Journal of the International Innovation Technology Exhibition & Conferences 2019 (Itec’19)

INTERNATIONAL JOURNAL OF
RECENT TECHNOLOGY AND ENGINEERING (IJRTE)

ISSN 2277 - 3878 | VOLUME 8 ISSUE 4 | NOVEMBER 2019

CONFERENCE
JOURNAL 2019

GEARING UP FOR INDUSTRY 4.0

2ND I N T E R N A T I O N A L I N N O V A T I O N
TECHNOLOGY EXHIBITION & CONFERENCE 2019

S E P T E M B E R 2 4 TH - 2 5 TH , 2 0 1 9

Journal of the International Innovation Technology
Exhibition & Conferences 2019 (Itec’19)

ISSN 2277-3878 |Volume 8 Issue 4 | November 2019

GEARING UP FOR INDUSTRY 4.0

September 24th - 25th, 2019
Kolej Kemahiran Tinggi MARA (KKTM) Kemaman
Organizer: Kolej Kemahiran Tinggi MARA (KKTM) Kemaman
Co-Organizer: Universiti Malaysia Pahang (UMP) and Universiti Kuala Lumpur
(UniKL)

International Innovation Technology Exhibition &
Conferences 2019 (Itec’19)

Conference Date: September 24th - 25th, 2019

Copyright @ 2020
Kolej Kemahiran Tinggi MARA (KKTM) Kemaman
All rights reserved. No part of this journal may be reproduced in any form except for
the inclusion of brief quotations in review, without permission in writing from the
author or publisher
Publisher:
International Journal of Recent Technology and Engineering (IJRTE)
Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP)
Bhopal (M.P.), India
ISSN 2277-3878 |Volume 8 Issue 4 | November 2019

International Journal of Recent Technology and Engineering (IJRTE)
Industrial Revolution 4.0: Volume 8 Issue 4, November 2019

International Innovation Technology Exhibition and Conferences 2019 (Itec’19)

LIST OF CONTENTS

TOPIC PAGE
10963-10970
EFFECTIVENESS OF E-LEARNING AND PERCEIVED SATISFACTION FOR
AN ACCOUNTING COURSE IN ENGINEERING USING THE FA4V1
HYBRID APPLICATION
Tengku Besaruddin Shah Tengku Yaakob, Wan Zuraida Wan
Yusoff, Che Alias Mohd Yusoff

ANALYTICAL MODELLING OF PREMISES-SPECIFIC SOLAR-ENERGY 10971-10974
ESTIMATION
K.A. Aznan, Sheroz Khan, Mashkuri Yaacob, Othman O Khalifa,
Ezzidin Aboadla

ASSESSMENT OF FRICTION STIR WELDING ON ALUMINIUM 3D 10975-10980
PRINTING MATERIALS
S.S.S. Abu Bakar, S. Sharif, Mohd Faridh

THE APPLICATION OF TAGUCHI METHOD IN OPTIMIZING 10981-10986
FABRICATION OF COMPOSITE PANEL FOR PARTICLEBOARD
M.N.M.Baharuddin, Norazwani Muhammad Zain, Eida Nadirah
Roslin, W. S. W. Harun

OPTIMIZATION OF FOAM-FILLED SQUARE THIN-WALLED ALUMINIUM 10987-10993
STRUCTURES
Nurul Izzah Ab Rahim, Salwani MS

DISCOVERING THE READINESS OF MALAYSIAN INDUSTRY IN 10994-10998
ADAPTATION OF INDUSTRIAL REVOLUTION 4.0 TOWARDS
MANUFACTURING SUSTAINABILITY
M.N.H.M. Rosdi, M.R. Muhamad, W.H.W. Mahmood, M.H.A. Kadir

i

EFFECT OF DRYING DURATION ON PRODUCTION OF SABAH SNAKE 10999-11002
GRASS (CLINACHANTUS NUTANS) BOTANICAL DRINK
Zaleha Ismail, Siti Nasiroh Ismail, Norehan Aziz

DEVELOPMENT OF SUSTAINABLE SUPPLIER SELECTION MODEL USING 11003-11006
DEMATEL FOR MANUFACTURING INDUSTRY
Norhafiza Mohamed, Wan Hasrulnizzam Wan Mahmood,
Muhamad Zaki Yusup, Rahayu Tukimin

PREDICTION OF DRIVER BEHAVIOUR IN DIFFERENT DRIVING PATH BY 11007-11010
USING ELECTRIC BUGGY CAR
Hasri Haris, Wan Khairunizam, Hafiz Halin

11011-11015

ICT INTEGRATION PRACTICES OF STEM TEACHERS IN TVET
Fariedah Lal Chan, Fitri Suraya Mohammad

THE MAKING OF PARTICLEBOARD FROM PALM OIL FIBER AND DUST 11016-11019
WOOD WITH EPOXY AS A RESIN
Siti Norzailina Md Som, M.N.M.Baharuddin, Norazwani
Muhammad Zain, M.R.Shaari

PRIORITIZATION OF SUPPLIER DEVELOPMENT PRACTICES: A FUZZY 11020-11024
METHOD
Rahayu Tukimin, Wan Hasrulnizzam Wan Mahmood, Norhafiza
Mohamed, Mohd Noor Hanif Mohd Rosdi, Maimunah Mohd
Nordin

SURFACE ROUGHNESS PERFORMANCE DURING MACHINING 11025-11028
ALUMINIUM ALLOY USING AUTOMATED COOLANT SYSTEM
Farizan Md Nor, Fairul Azni Jafar, Mohd Hadzley Abu Bakar, Wan
Nur ‘Izzati Wan Md Hatta

DIGITAL INTERACTIONS AND INTERNATIONALISATION OF SMALL, 11029-11034
MEDIUM ENTERPRISES
Azlina Mohamad, Adriana Mohd Rizal, Rohaida Basiruddin,
Suzilawati Kamarudin

ii

International Journal of Recent Technology and Engineering (IJRTE)
ISSN: 2277-3878, Volume-8 Issue-4, November 2019

Effectiveness of E-Learning and Perceived
Satisfaction for an Accounting Course in

Engineering using the FA4v1 Hybrid
Application

Tengku Besaruddin Shah Tengku Yaakob, Wan Zuraida Wan Yusoff, Che Alias Mohd Yusoff

 competitive. Industry 4.0 which began in 2016 reflects the

Abstract. The purpose of this study is to determine the discovery of new technologies such as automation, Internet of

effectiveness of adapting e-learning using self-developed hybrid Things (IoT), analysis and big data, simulations, system

applications called FA4v1 based on IR4.0 technology for an integration, robotics and cloud utilization that will bring the
accounting course in Politeknik Sultan Haji Ahmad Shah
(POLISAS). A hybrid FA4v1 application was self-developed by the development of the modern world landscape. According to
content creator that works on mobile and web technologies. It has
Ahmad Sobri [1], m-learning has long been practiced and

been implemented for students taking Financial Accounting 4 in implemented in developing countries such as the United

the December 2018 session. This study attempts to evaluate, 1) the States as well as European countries. The development of the
perceptions of the students (application user) on the hybrid FA4v1
usage, and 2) It also evaluates the impact of its usage and IR4.0 is pushing for changes in teaching and learning (TnL)
application in reflecting final examination results for Financial
technology to realize Educator 4.0 which can apply cloud

computing technology as one of the teaching and learning

Accounting 4 course A questionnaire was distributed online for methods. The integration of web2.0 applications will add

users to give their feedback after using the application in their value to the quality of teaching while also opening up space
class. It consists of student’s perceptions involving time, tools and
for self-learning and collaborative learning.
costs compared to conventional teaching and learning (TnL)
methods. The study showed that more than 80% give their positive Mobile devices have become important in the IR4.0

feedbacks in using the application. They agreed that the teaching and learning (TnL) environment which is the

application is easy, efficient, and cost-saving compared to other education communities used the mobile phone as storage, to

Teaching and learning methods and will benefit them as an process and retrieve information anytime and anywhere.

alternative learning resource. The study uses a Rafidah [25] revealed that most of the students have a

causal-comparative design which consisted of experimental group smartphone and they are most likely prefer to use their

(application user) and control group (non-application user) that smartphone for learning purposes. The researchers have

shows an increase in the number of passes for the course from chosen financial accounting 4 (FA4) the subject that she

23.5% to 52.9%. The study is useful in providing templates for taught to apply mobile learning application in TnL that

educators to self-develop their own contents in providing a supports IR4.0 because the researcher has expert content in
blended learning approach to enhance student’s knowledge. It

was also found that the use of IR4.0 technologies such as cloud this subject. This application was developed base on a mobile

computing will make such a great impact on the development of learning concept that integrates cloud application and smart
Education 4.0.
application.

In Malaysia, m-learning practices are not widely used

Keywords: E-learning, mobile application, M-learning, compared to in Europe and the state of America. Issham
Accounting Education
Ismail [26], the study revealed that an overwhelming

I. INTRODUCTION majority of students in Malaysian public universities were

The Fourth Industrial Revolution (IR4.0) involves the still moderately ready for mobile learning. Many of them

technology system of physical cyberspace creates a new seemed to be not quite familiar with such a learning
challenge for all sectors in Malaysia that require them to make
changes in line with the digital transformation to remain approach even though there is an interest among them to

learn more about mobile learning. The study from Filiz

Angay Kutluk [27] most of the students who have used mobile

devices for learning and educational purposes or made

research/homework about accounting lessons with cell phone

and handheld computer and spent more time on mobile

Revised Manuscript Received on November 19, 2019 devices for learning and education on daily basis, think that
* Correspondence Author
using mobile devices for learning purposes would be easy and
Tg Besaruddin Shah Tg Yaakob*, E-learning Officer, Politeknik
Sultan Haji Ahmad Shah, Kuantan, Pahang, Malaysia. Email: they intend to use it because of the immediate access to
[email protected]
information, and would enable them to make
Wan Zuraida Wan Yusoff*, Senior Lecturer, Commerce Department,
Politeknik Sultan Haji Ahmad Shah, Kuantan, Pahang, Malaysia. Email: research/homework about accounting lessons more quickly,
[email protected]
using mobile devices for making
Che Alias Mohd Yusof*, Deputy Director (Academic), Politeknik
Sultan Haji Ahmad Shah, Kuantan, Pahang, Malaysia. Email: research/homework about
[email protected]
accounting lessons would help

Retrieval Number: D5416118419/2019©BEIESP 10963 Published By:
DOI:10.35940/ijrte.D5416.118419 Blue Eyes Intelligence Engineering
& Sciences Publication

Effectiveness of E-Learning and Perceived Satisfaction for an Accounting Course in Engineering Using the FA4v1
Hybrid Application

them perform their studies anyplace. First, the fast-growing technology and telecommunication
For this study, the authors had developed an application systems require education institutions to make changes in line
with the digital transformation to remain competitive.
that supports IR 4.0, the hybrid FA4v1 application which Second, in line with IR4.0, the 4th surge in the Malaysian
focuses on the use of Cloud Computing technology, one of the Education Development Plan (Higher Education) aims to
cores of IR 4.0 as a Teaching and learning application. This produce quality TVET graduates which are based on new
application used concepts of m-learning which is part of teaching and learning methodologies, responsive and
e-learning that integrates cloud and mobile phone sustainable governance, applied research and innovation
applications. approaches and talent technology-driven. Due to these
situations, Malaysia really requires an educational institution
II. PROBLEM STATEMENT to improve the teaching and learning method in line with
IR4.0 to produce competitive and high quality of graduates.
This action research is triggered by lecturers' concerns to
know the level of students' understanding in the classroom in III. LITERATURE REVIEW
real-time, as soon as a topic is taught. Lecturers are also
unable to know the extent of the student's self-learning A. Introduction
process. Problems also arise because of no platform suitable
for two-way communication between students and lecturers Nowadays educational system has undergone another
other than communication in the classroom. evolution of educational technology when m-learning is
introduced to raise the level of TnL Its use has made TnL
To solve this problem, a hybrid application has been easier for students and lecturers. Many local and foreign
developed which is a mobile phone application integrated researchers have tried to see how effective the use of
with the cloud computing technology to facilitate students to m-learning in TnL.
access lecturer notes, conduct evaluation and communication
processes between lecturers and students. The researchers Definitions: Lan & Sie [5], m-learning is interpreted as a
took consideration in times saving, friendly used, cost-saving, kind of learning model that allows students to get learning
self-learning, TnL can be performed anywhere, interesting materials anywhere and anytime with mobile technology.
learning and efficient. According to Belias D. [21], although Parsons [8], attributes that m-learning is part of e-learning and
different studies have looked into student responses towards distance learning. If m-learning is linked to the internet and
modern teaching tools and their effectiveness measured in wireless, it is not much different from the original concept of
terms of student performance in final exams, there are issues e-learning. Oller [14], stated that similar to e-learning,
pertaining to such tools that are still unclear. It is noticeable m-learning also takes place in the classroom but what
that many students report a preference for personalized distinguishes m-learning allows the learning process to
teacher-centered teaching methods and suggest the use of the happen not only in the classroom but everywhere at any time.
above modern teaching tools and practices as ancillary tools, According to Margaret et al., [15], Cloud Computing in a
only. In light of the above, it could be argued that modern simple sense is to store and access data and applications using
teaching methods, strategies, and tools should adopt and the Internet other than computers. Such as documents,
integrate Information and Communication Technologies on pictures, audio or video. Users can access such data by using
the premise that the latter is adapted to each student any computer or another mobile device by using Internet
population’s interests, abilities, and ambitions. access. According to Suzita [29], Cloud Computing in simple
definition is to store and retrieve data and applications using
This study would like to explore the students’ perspectives the internet. Examples of data stored are documents, images,
related to m-learning tools in the teaching and learning videos, and audios. Users can retrieve those data using any
process and its’ effectiveness. This study going to answer computers or mobile devices with an internet connection. Lee
these following research questions: Badger [22] Cloud computing is a model for enabling
convenient, on-demand network access to a shared pool of
1. What are the perceptions of the students (application user) configurable computing resources (e.g., networks, servers,
on the effectiveness of hybrid FA4v1 usage? storage, applications, and services) that can be rapidly
provisioned and released with minimal management effort or
2. What is the performance of the two groups of service provider interaction.
respondents in the final exam?
a. The control group (non-application user) B. E-learning in Teaching and Learning
b. The experimental group (application user)
According to Salem et al., [9], the use of the e-learning
3. Is there a significant difference between the final system positively affects the individual impact. The analysis
exam scores of the control and experimental group? of the results shows that using the e-learning system has
increased students’ ability to interpret the information
A. Research Objective accurately. Furthermore, the e-learning system has increased
students’ understanding of the information and relevant
In General, this study is to determine the effectiveness of activities. It also helps provide basic information, which, in
adapting e-learning using self-developed hybrid applications turn, helps students make important decisions effectively and
called FA4v1 based on IR4.0 technology for an accounting accurately, thus increasing the overall productivity of the
course in Politeknik Sultan Haji Ahmad Shah (POLISAS) process of teaching and
Kuantan, Pahang, Malaysia. The main objective of this study learning.
is to investigate the students’ perceptions and evaluating the
impact of using the hybrid FA4v1 in Financial Accounting 4.

B. Significance of the Study

This study on evaluating the effectiveness of e-learning and
perceived satisfaction for an accounting course using the
FA4v1 hybrid application is noteworthy on several grounds.

Retrieval Number: D5416118419/2019©BEIESP 10964 Published By:
DOI:10.35940/ijrte.D5416.118419 Blue Eyes Intelligence Engineering
& Sciences Publication

International Journal of Recent Technology and Engineering (IJRTE)
ISSN: 2277-3878, Volume-8 Issue-4, November 2019

Mohd Shoaib & Aditya [13] founds that the role of a mobile modern teaching method are more than those attitudes toward
learning application is increasing among students learning. the traditional teaching method. Avanish K. S and
The results indicated that mobile learning application can be Mohammed I.S [23], respondents showed positive responses
very useful in the higher education environment. toward technology-based teaching as compared to traditional
Furthermore, the results showed that the students had classroom teaching and students believed that
adequate knowledge and awareness to use mobile technology technology-based teaching helped them in solving accounting
and the Internet in their educational environment. problems better. Khaled D. [30], the study addresses the
feasibility and effectiveness of using unconventional
Johan et al., [4], indicating that most of the respondents technologies in delivering accounting knowledge.
were exposed to e-learning and among the reasons they
preferred to learn via e-Learning where it provided them All the past studies in conventional versus Technology
greater flexibility to select either instructor-led or self-study base education in TnL showed that students prefer to have
courses and enabled them the flexibility to learn at any place technology base education compare to conventional because
and time. of flexibility in terms of time and place and more efficient.

Irwanto [3], students are using smartphones to support the D. Research framework
learning program inside and outside the classroom. The study
found that students prefer to use smartphones in learning The research framework theory is based on the ideas of
because of the availability of access to information ar anytime previous researchers such as Khalil & A. Elkhider [6], the
and everywhere without the limitation of space and time. effectiveness of the systematic approach in designing
instruction provides an empirical and replicable process for
Shital P. B and Pankaj B.D. [28], Electronic Learning or reliable assessment to continuously and empirically improve
E-learning incorporates all forms of online instruction using the developed learning experience.
personal computers-learning is the follow up of E-learning
which for its part originates from D-learning (Distance Andreea & Catalin [2], found that continuing to learn and
learning). The term `m-learning' has lately emerged to be try new methods of communication will aid in improved
associated with the use of mobile technology in education. learning and foster teacher-student respect and collaboration.
Mobile learning simply means "learning on the move'. In There are effective techniques for presenting face-to-face
other words, the new term simply attempts to differentiate material in the online environment that will allow the student
between learning that takes place in a formal context such as a to achieve a higher level of satisfaction of learning and
classroom. In this, the learning process takes place anytime, cognitive understanding of the course material.
anywhere while we are moving in our environment.
Most past researchers found that e-learning in teaching and Mousazadeh [7] studied that the overall benefits of
learning gives a positive impact on the students which is e-learning include the promotion of learning, independence,
increasing the effectiveness in TnL and the process of TnL and individual satisfaction, learning at anytime, anywhere and
more flexible in terms of time and place. with any background, learning without the same prerequisites,
speed and process of learning due to individual needs,
C. Conventional versus Technology base education in individual learning along with cooperative learning, saving
TnL time and costs significantly, the possibility of teaching and
learning for all people, mutual teaching and learning, getting
Students prefer to have a modern and technology base quick results in learning and learning more by using
teaching method compare to the traditional method because of multimedia and maintaining resources. The conceptual
time-saving and more efficient. The study from Rehab U.T framework of the study is shown in figure 1.
[22], proved that Accounting student's attitudes toward the

Fig. 1.Conceptual Framework of the Study

IV. METHODOLOGY integrated with the cloud computing technology to facilitate
students' needs. This study explored the effectiveness of
A. Introduction FA4v1 apps to accounting students. According to Ramen M
and Jugurnath B. [24], takes into consideration factors and
FA4 is a suitable subject for m-learning apps which is this types of method used, on the learning process and the study
subject need student to gather learning materials at anywhere observed that the student prefer modern tools alongside with
and anytime because students need to do fieldwork at the the traditional face to face to cope with accounting studies.
company for their case study. This subject requires students The perceived this ‘Hybrid method’ as a must to get the best
to always refer to the accounting standard during their of themselves as they can review online material according to
learning process so m-learning apps will assist them anytime their flexibility and
and anywhere. A hybrid application called FA4v1 apps has conveniences in case they unable
been developed which is a mobile phone application to attend classes, less time spent

Retrieval Number: D5416118419/2019©BEIESP 10965 Published By:
DOI:10.35940/ijrte.D5416.118419 Blue Eyes Intelligence Engineering
& Sciences Publication

Effectiveness of E-Learning and Perceived Satisfaction for an Accounting Course in Engineering Using the FA4v1
Hybrid Application

on travel and on-campus and no time constrained and can effectiveness and its impact in assisting their comprehension
learn at their own place. Result proved that student preference in learning the course.
for Traditional and Modern methods are almost the same but
also perceived hybrid as innovative ideas that should be
promoted.

B. Research Design

This study has seven (7) phases in the research design,
refer to figure 2. Phase 1, 2, 3 and 4 conducted in session June
2018 (June – November 2018). Phase 5, 6 and 7 are
conducted in session December 2018 (January – June 2019).

Fig. 3.Population and sample.

Fig. 2.Phases in the Research Design D. Research Instrument

The hybrid FA4v1 application not only uses the m-learning Two (2) types of Instruments are used to evaluate the
concept but it has been integrated with the use of cloud effectiveness of the FA4v1 application.
applications. This action research utilized the 1. Questionnaire: This study used the survey method for data
experimental design since its main purpose was to
determine the effectiveness of mobile learning applications collection to evaluate the perceptions of the app's user on
in the FA4 class and its possible effect on the achievement the hybrid FA4v1 usage. Items in the questionnaire were
of two groups of students which are non-application built to ensure that the information required for achieving
users and application users. Both groups were taught the the objectives. The instrument was built by using a Likert
same lessons for a semester. The control group was scale (scale 5 strongly agrees and 1 strongly disagrees). The
taught using traditional teaching with a similar activities questionnaire is divided into two sections in which the first
approach while the experimental group was given FA4v1 section is the answer for the research questions and the
application and taught in class by using the FA4v1 second section is the overall comments from respondents.
application. Test reliability of the instrument has been made to this item
by using Cronbach alpha (maximum value is 1). Based on
C. Population and Sample Guilford [20] stated that Cronbach's Alpha must be ≥ 0.70,
The population of the study is Semester 5th students for items <10 is an indicator that a satisfactory level of
reliability. The analysis of the data value of the reliability
Diploma in Accounting Program, Politeknik Sultan Haji coefficient for this study is 0.994.
Ahmad Shah (POLISAS) from session June and December 2. Assessment (final examination): Question is to evaluate the
2018, refer figure 3. Two (2) different batches are selected impact of application usage in the final examination result
because to have the same lecturer for the experimental group for the Financial Accounting 4 course. Both batches used
and control group. The sample for both groups was selected the same Final Examination Instrument Standard Table
base on the same achievement level in Financial Accounting 3 (FEIST) to ensure both batches have the same level of
(FA3). The clustered sample is used in this study which is two question difficulties.
(2) sections from Diploma in Accounting students from
Session June and December 2018 as subgroups of the E. Data Analysis
population. This is single-stage cluster sampling, all members
of the chosen clusters are included in the study. FA4v1 apps For the data analysis, a statistical tool from the Statistical
have been provided to semester 5 Section 1 from session Package for the Social Sciences (SPSS) version 17 was used
December 2018 which is consists of 17 students as a group to analyze the data from the survey method. Sekaran [17],
selected as a sample. They were instructed to use the stated that specific steps utilized for the data analysis, which is
application during their TnL process and evaluate the editing the data, methods of handling blank responses, coding
data, categorizing data, creating the data file and
programming.

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DOI:10.35940/ijrte.D5416.118419 Blue Eyes Intelligence Engineering
& Sciences Publication

International Journal of Recent Technology and Engineering (IJRTE)
ISSN: 2277-3878, Volume-8 Issue-4, November 2019

V. DATA COLLECTION AND ANALYSIS This questionnaire discusses these issues in eight
questions.
A total of 17 samples from control and experimental
groups were selected based on the same achievement in FA3, Descriptive statistics for the eight items of students’
refer to Table I. perceptions of the hybrid FA4v1 usage are shown in Table II,
including the percentage in each response category and the
Table- I: The Group’s achievement in the FA3 final overall means and standard deviations. The items rated as
examination. most satisfaction were implementation of learning through
this system saves costs especially the cost of printing and
Marks range Control group* Experimental buying books (M = 4.65, SD = 0.49), Learning can be
group** (%) implemented anywhere using smartphone (M = 4.65, SD =
(%) (%) 0.49) and the load to the classroom is decreased as there is no
0 (0) need to bring textbook to class (M = 4.65, SD=0.49). The
0 - 10 0 (0) 0 (0) items rated as satisfaction were the process of accessing notes
3 (17.6) through the FA4v1 application is much easier than the manual
11 - 20 0 (0) 5 (29.4) (M = 4.59, SD= 0.51), the contents in the FA4 v1 application
is very useful for learning, revision and reinforcement
21 - 30 5 (29.4) 6 (35.3) sessions. (M = 4.41, SD = 0.51), the process for accessing
3 (17.6) notes via the FA4v1 application is faster than the manual
31 - 40 4 (23.5) method (M = 4.35, SD=0.49), self-learning process through
0 (0) the application system FA4v1 is exciting (M = 4.35, SD =
41 - 50 4 (23.5) 0 (0) 0.49) and the FA4v1 application is very user friendly (M =
0 (0) 4.35, SD = 0.49).
51 - 60 3 (17.6) 0 (0)
17 (100) B. Second Instrument
61 - 70 1 (0.06) The 2nd instrument used to answer the second and third

71 - 80 0 (0) research questions by using the final examination paper. Both
groups need to sit for the final examination of FA4 at the end
81 - 90 0 (0) of the semester. The assessment question is to evaluate the
impact of application usage in the final examination result for
91 - 100 0 (0) the FA4 course.

Total students 17 (100) Marks from students’ achievement in the final
examination for the control and experimental group are
* Non-app user

**App user

A. First Instrument

The instrument used to answer the first research question
by using questionnaires. The survey was completed by the
experimental group (application user).

The questionnaire was designed to get students'
perceptions about the use of FA4v1 hybrid applications. The
issues discussed are related to the process of accessing notes
in terms of time and easier, cost-effective, study implemented,
application contents and study satisfaction.

Table-II. Means, Standard Deviations, and Percentage of Respondents (N = 17).

Item M SD Strongly Disagree Neutral Agree Strongly
Disagree 41.7 Agree
58.3
a The process of accessing notes through the 66.7
33.3
FA4 v1 Application is much easier than 4.59 0.51 0 0 0 33.3
66.7 50
the manual method. 33.3 33.3
33.3 66.7
b The process for accessing notes via the 66.7 58.3
58.3 33.3
FA4v1 Application is faster than the 4.35 0.49 0 0 0 41.7

manual method

c Implementation of learning through this

system saves costs especially the cost of 4.65 0.49 0 0 0

printing and buying books.

d The self-learning process through the FA4 4.35 0.49 0 0 0
v1 application is exciting.

e Learning can be implemented anywhere 4.65 0.49 0 0 0
using smartphone.

f The load to the classroom is decreased as

there is no need to bring the textbook to 4.65 0.49 0 0 0

class.

g The FA4 v1 application is very user 4.35 0.49 0 0 0
friendly

h The content in the FA4 v1 Application is

very useful for learning, revision and 4.41 0.51 0 0 0

reinforcement sessions.

Retrieval Number: D5416118419/2019©BEIESP 10967 Published By:
DOI:10.35940/ijrte.D5416.118419 Blue Eyes Intelligence Engineering
& Sciences Publication

Effectiveness of E-Learning and Perceived Satisfaction for an Accounting Course in Engineering Using the FA4v1
Hybrid Application

Table-III. Students' achievement in final examination FA4.

FREQUENCY/NUMBER OF STUDENTS Total

MARKS RANGE 1 -10 11 - 20 21 – 30 31 - 40 41 -50 51 - 60 17
Non-application user 17
0 7 2 4 2 2
Application user 0% 41.1% 11.8% 23.5% 11.8% 11.8%
0
0% 0 3 5 6 3
0% 17.6% 29.4% 35.3% 17.7%

Table-IV. The number of student pass/fail in final examination FA4.

FREQUENCY/NUMBER OF STUDENTS Total

MARKS RANGE 1 -39 marks (Fail) 40 – 100 (Pass) 17
Non-application user 17
13 (76.5%) 4 (23.5%)
Application user 8 (47.1) 9 (52.9%)

shown in Table III and Table IV. The percentage of students Lecturers can also monitor the student's self-learning process
in the lowest range of 1– 20% for the non-app’s user is 41.1% through the cloud.
2) Second research question: What is the performance of
compare to application users 0%. The percentage of students the two groups of respondents in the final exam? a) The
in medium-range 21 - 40% for the non-app’s user is 35.3% control group (non-application user) b) Experimental group
(application user).
and for application, the user is 47%. The percentage of
The study showed that students have a positive impact on
students in the high range for this table 41 - 60% for the the final examination result after using the application. The
non-app’s user is 23.6% and for application, the user is number of students passes in the FA4 final examination
increased by 29.4% after using the hybrid FA4v1 application
53.2%. and the number of students fails decreased by 29.4%. The
number of students who obtain marks to range 1-20% is 0%
Table IV shows the total students fail and pass for both after used the application compare to before use the
groups. The percentage of students fail for the non-app’s user application is 41.1%. The number of students increased in
high marks (51-60%) after using the application is 17.7%
is 76.5% and for application, the user is 47.1%. The compared to before which is 11.8%.
percentage of students pass for the non-app’s user is 23.5% 3) Third research question: Is there a significant difference
between the final exam scores of the control and experimental
and for application, the user is 52.9%. group?

VI. RESULTS AND DISCUSSION This result indicates there is a significant difference
between the final exam scores of the control and experimental
1) First research question: What are the perceptions of the group because of the application used. The experimental
students (application user) on the effectiveness of hybrid group used the hybrid FA4v1 application and showed the
FA4v1 usage? improvement in examination result. The total student pass is
increased and fail decreased after used the application. The
The result revealed that all the respondents have positive overall percentage of students pass the examination is 53%
perceptions of the application. All the satisfaction measured for application users compare to non- application users that is
is a high level of satisfaction which is more than the score 23.6%.
means of 4.0. According to Azizi [19], the means score
consists of three scoring level and Table V shows the mean VII. CONCLUSION
score description. The study proved that all the respondents
agreed that the FA4v1 apps effective and efficient in the This study was conducted for evaluating the effectiveness
teaching and learning process. of e-learning and perceived satisfaction for an accounting
course using the FA4v1 hybrid application. The finding
Table- V: Level of Assessment Based on Means Score reveals that by using m-learning tools such as FA4v1 hybrid
application will make Teaching and learning more effective
Means Score Level and give more satisfaction to the students. This is supported
1.00 - 2.33 Low by Safiyeh [10], agrees that e-learning has a significant role in
2.34 - 3.66 Medium the instruction of students in higher education. Their study has
3.67 - 5.00 High confirmed that e-learning is an element that affects students’
motivation.
After using the FA4v1 hybrid application and also Cloud
Computing, the Teaching and learning process becomes more They also found that there is a positive impact on the final
effective and efficient. Lecturers use cloud computing to examination result and there is a significant difference
update notes and exercise questions into FA4v1 hybrid between the final exam scores
applications. The FA4 v1 hybrid application in the mobile of the control and
phone is a platform for students to access all notes for the FA4 experimental group after using
course as well as exercise questions to test students'
understanding of the subject in which they have been taught.
Lecturers and students will see the achievements and levels of
understanding in real-time. The process of communication as
in the classroom takes place anywhere and at any time.

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the application. The finding reveals that using m-learning 14. Oller, R. 2012. The future of mobile learning (Research Bulletin).
applications will make Teaching and learning more effective Louisville, CO: Educause Center for Analysis and Research.
and improved the student's performance. The results are DOI=http://net.educause.edu/ir/library/pdf/ERB1204.pdf.
supported by Tomas et al., [12], confirmed that the provision
of the e-learning tool for students has got a positive influence 15. Kuderna I., Benta M., Cremene and Razvan P. 2004, Multimedia
on their test results. m-learning using mobile phones. A book of papers from MLEARN
2004 pg (27 -28).
The limitations of this study are on the small sample of
students that have taken the course and use the application as 16. Arrigo M., Manuel G., Davide T., Giorgio C. and Domenico T. 2014.
it can be extended to other classes. For the next research, it is mCLT: an application for collaborative learning on a mobile telephone.
recommended that the control and experimental group is A book of papers from MLEARN 2004 pg (11 -15).
selected from the same batch. The researcher also believes
that this research provides a bigger perspective to the higher 17. Sekaran, U. 2003. Research methods for business: A skill-building
education institution on the importance of m-learning tools approach (4th ed.). New York, NY: John Willey & Sons.
because Malaysia really requires education institutions to
improve teaching and learning methods in line with IR4.0 to 18. Benta D., Bologa G., and Dzitac, I. 2014. E-learning Platforms in
produce educator 4.0. Higher Education. Case Study, 2nd International Conference on
Information Technology and Quantitative Management (ITQM),
ACKNOWLEDGMENT Procedia Computer Science 31(2014) 1170 – 1176.

Our thanks to the Department of Commerce, Politeknik 19. Azizi Y., Shahrin H., Jamaludin R., Yusof B., and Abdul R.H. 2007.
Sultan Haji Ahmad Shah, Kuantan, Pahang for allowing us to Menguasai Penyelidikan dalam Pendidikan: Teori, Analisis &
conduct the studies on the effectiveness of using the FA4v1 Interpretasi Data. Kuala Lumpur: PTS Professional Publishing Sdn.
hybrid application to Diploma in Accountancy program as Bhd.
part of the National e-Learning Policy initiatives.
20. Guilford. J.P.(Ed.).1954. Psychometrics for Social and Personality
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11. Signe S. N. and Rikke Ø. 2015. The effectiveness of E-Learning: An 30. Khaled D., Eskandar T. and Sherif K. 2017. The Use of IT in Teaching
Explorative and Integrative Review of the Definitions, Methodologies, Accounting in Egypt the Case of Becker Conviser. International
and Factors that Promote e-Learning Effectiveness. Electronic Journal Conference ICTO2017 – ICT for a better life and a better world, Paris
of e-Learning Volume 13 Issue 4 2015page 278- 290. March 16-17, 2017.

12. Tomáš M., Petr Š., Petr V. 2015. The Influence of Using E-Learning AUTHORS PROFILE
Tools on The Results of Students at The Tests. Procedia - Social and
Behavioural Sciences 176 (2015) 81 – 86 Author-1 Tengku Besaruddin Shah Tg Yakkob currently
Photo working as Senior Lecturer at Politeknik Sultan Haji
13. Mohd Shoaib A., Aditya T. 2018. An Investigation of Effectiveness of Ahmad Shah, Kuantan, Malaysia. Holds Bachelor in
Mobile Learning Application in Higher Education in India. Rf=
https://www.researchgate.net/publication/319187545 Mechanical Engineering from MARA Institute of

Technology, Shah Alam, Selangor, Malaysia. Registered

with Board of Engineers Malaysia (BEM), Institution of

Engineers Malaysia (IEM) and Institution of International Engineers (IIE)

and also committee member with BIM Institute of Malaysia. Appointed as a

E-learning officer which is responsible for managing e-learning initiatives
and activities in the institution.. 1st achievement is Silver Medal award in the

National Innovation Competition in 2019.

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Effectiveness of E-Learning and Perceived Satisfaction for an Accounting Course in Engineering Using the FA4v1
Hybrid Application

Wan Zuraida Wan Yusoff currently working as Senior
Accounting Lecturer at Politeknik Sultan Haji Ahmad
Shah, Kuantan, Malaysia. Master in Technical Education
hpoulbAdleiPucrthahoitonitoro-nB2afochr erleosrferaoormfchAUwccnooriuvkne. rtAasinstcsyoycTfiareotcemhnMoUelnomigvbyeerrsooiftfyMMPaaulltaaryayssoiiaafnMaInnadsltaiydtuseitgaer.eo9ef
Accountants (MIA) since 2013 until now. 1st achievement is Silver Medal
award in the National Innovation Competition in 2019.

Che Alias Mohd Yusoff currently working as Deputy
Director of Academic at Politeknik Sultan Haji Ahmad
Shah, Kuantan, Malaysia. Completed his Bachelor in
Civil Engineering University of Glasgow, Board of
Engineers Malaysia.

Author-3
Photo

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Analytical Modelling of Premises-Specific Solar-
Energy Estimation

K.A. Aznan, Sheroz Khan, Mashkuri Yaacob, Othman O Khalifa, Ezzidin Aboadla

Abstract: Solar energy is great potential for future energy DC microgrid system is a system that generate energy
due affordability of solar related panels and equipment. Solar- supply at one spot and the energy is used domestically for
Energy Microgrid for serving DC and AC loads of areas under everyday use. The advantage of having DC microgrid is to
consideration. Microgrid is a new concept for making safe, reduce the energy loss from the long distance transmission
clean, and renewable solar available for use. Most of the line normally raised and setup in the conventional AC
countries have developed it solar farm in order to harvest the transmission system. Such generation of renewable energy
energy and make it useable for daily use. This energy can be is genuinely referred to as Distributed Generation, as it
used either for premises-specific loads and also distributed to provides for the variable load from sources which are
other regions through the national grid through what is called random in nature [2-5]. The research focus here at how to
Distributed Generation (DG). Estimating solar energy potential model a variable load target area before proposing to install
estimation of premises under target is obviously an exercise that DC microgrid from solar sources of generation. The DC
may prove in the design of such DG microgrids. This paper microgrid installed at one spot will be directly, efficient and
presents two analytical modelling approaches for estimating the reliable to that location [6]. This paper present analytical
solar energy potential of a given geographical location. The two modelling and mathematical approach to the solar energy
approaches are explored for estimation two very closely related harvested using the laboratory testbed installed in Advanced
amount of solar energy in kWh for eleven hours of time of a day Technology Training Centre (ADTEC) in Kg Payoh,
using Heliocentris Hybrid Energy Lab-System data. The Kemaman Terengganu, Malaysia. The contribution of the
approaches may find utility in the pursuits of the renewable work consists of using piece-wise linear approach used in
energy estimation needed for designing PV-solar microgrid. The analytical modelling of the generation potential and then
mismatch of 6.31% energy estimation between the two suggesting a relevant integrated microgrid structure for the
approaches may be due to parametric complaint inaccuracy required power generation, estimating ultimately designing
instead of the approaches employed. the target standalone microgrid system for the target area.

Keyword: microgrid, distributed generation, renewable II. METHODOLOGY
energy
a) Installation of Energy Lab
I. INTRODUCTION
ADTEC Kemaman is located in Kg Payoh, Kemaman,
Solar energy is one of the sources of renewable energy that Terengganu on area of the size of 100 acres. It is one of the
has been used widely. The unlimited source of solar training centres in Malaysia, built up for the Technical and
available makes it one of the largest energy harvests next to Vocational Education and Training (TVET) in order to train
wind energy potential. Using renewable energy leads to students to become technologists. The energy lab has been
reduction in losses incurred due to transmission and installed in one of the buildings for the students to study and
distribution systems. The intermittent nature of renewable learn skills regarding the installation of solar panels and
energy makes it highly unreliable and research is underway related electronic equipment for generation of solar energy.
to make it as a source providing consistent power. The energy solar panel has capacity of 25.3V and the
The sun shines brightly for nearly 365 days per year with current ISC to be rated at 8.52A. The panels are fixed
the penetration of light through space reaching the earth‟s mounted with one of the panels is facing the direction of 45
surface for almost 10 to 12 hours at one location in most degree to the West and tilt 85 degree to the sky and another
parts of Malaysia which makes it as one of the potential of panel is facing 45 degree to the East and tilt 45 degree to the
harvesting energy sources for domestic supply sources. The sky. The hybrid energy lab system is consist of equipment
energy so received may be even made to be distributed to for the Renewable Energy System (RES) which the source
the nation through the direct current (DC) standalone are from solar, wind, fuel cell (hydrogen) and energy
microgrid system or be fed by tying it to the national grid storage system.
[2]. b) Distributed Generation (DG)
Distributed Generation (DG) is said to be the installation
within the network to reduce the need of transmission and
high voltage distribution system. Microgrid is a concept
connecting large number of distributed power generation
sources, particularly renewable
energy sources of solar, wind,
biomass, oceanic tidal, and

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Analytical Modelling of Premises-Specific Solar-Energy Estimation

microturbine hydroelectric together for serving local and local load. The excessive power flow from the DG will
national load. In the case of local load, it stays most of the then directed to the energy storage system (ESS) in order to
time as DC, while in the case of serving national, the charge the battery packs to be at the maximum power rating.
microgrid is tied for the integration to the national grid Also, whenever the power is needed to be supplied to the
supply at the low voltage distribution level. This trend of national grid, it can be converted to AC when power is
technology is on the rise due to the renewable energy required to be sent along the AC bus to the national grid
products affordability and evolving living priorities due to [15].
environmental group‟s pressure for pollutants reduction
[7][8].

Fig. 2. Distributed Generation for DC Microgrid

Fig. 1. Location of Photovoltaic (PV) Solars Panels Fig. 3. Control Strategy for the Power Flow

Installation As for the DG, the intermittent nature of power is the
challenge issue for renewable energy sources. For example
The DG structures have got its merits of the assets on spot the changes of climate from bright sunny days to cloudy and
utilization, enhanced power quality by being available, and also from day to night for the solar will affect the power
better system reliability by avoiding mixing with the generation and as well as the wind turbine will depend on
systems, flexibility by being added/removed easily, and the speed of change of wind. Therefore, during the
capacity using modular structures in integrated fashion. intermittent, in order to maintain the DC bus at a certain
Such structures give rise to what are started known by the level, the control will then send the power from the ESS
names of micro-grids. Microgrids have the preferential back to the DC bus and so that the interruption of the power
benefits of being islanded easily in the case of accidental or loss is recovered.
transitional conditions on the main grid system. Also,
conceptually microgrids are better modularly structured for III. RESULT AND DISCUSSION
inter-connectivity before getting integrated with the system
as shown in Figure 2. In the islanded mode, the system a) Modelling of PV- Power Capacity
needs to control the sharing of load with different units and
to balance the power in the microgrid. To achieve arriving Solar power generation depends on the temperature as well
at such aims is done by using the centralized or as irradiation of solar energy alongside solar panels
decentralized power management [13]–[17]. The centralized orientation of the target area of ADTEC Kemaman, one can
method of control strategy will rely on the communication estimate the solar potential of area under consideration
between sources and the loads which reduce the reliability (AUC) using the technique of [16]. In this work is used data
of the system [18], something has to be addressed. of Heliocentris Hybrid Energy Lab-System source as shown
Decentralized control method through using a chain of in Figure 4, which is linearly approximated to what is as
converters however requires local measurements and also shown in Figure 5.
the non-crucial communication can be used in order to
achieve other aims such as restoring voltage and frequency
deviations. This work addresses the features any future
renewable energy converter chains are expected to be
equipped with such that it an emergency situation they
adapt to performing in roles supporting the on-going system
problems of voltage compensation instead of islanded
altogether.
The control of power flow in the DG embedded system is
needed in order to turn ON and OFF the power converters in
a way of effectively targeting the aims priory mentioned
aims. This strategy is needed so that the DC bus as shown
in Figure 3 can be maintained at a certain level so whenever
the load demand is needed in serving the local load leading
us to control the energy power from either the DG such as
solar, wind, fuel cell or wind turbine will be directed to the

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ISSN: 2277-3878, Volume-8 Issue-4, November 2019

Fig. 4. Power generation for the period of 07.00am to The above total power can be worked by the integration
06.00pm mathematical calculation after having represented the PV-

Figure 4 shows the power that has been generated from the solar plot of Figure 4 by linear segments as shown in Figure
PV for the period of eleven hours starting from 07.00 am to 7. Every segmental line can be expressed by a slope „m‟ and
06.00pm. y-intercept „c‟ of linear equation of = + , using
which we obtain what is given as under:

( ) = 0.57 – 4.26
( ) = 0.64 – 5.14
( ) = −0.53 + 10.47
( ) = 0.9 − 10.30
( ) = −0.3 + 7.70
( ) = −0.8 + 15.40
The area under the lines (a)-to-(f) are estimated by using
ordinary integration formulas will be used and the integral

of the equations shall be sum up in order to get the total
energy generated in kWh.

Fig. 5. PV-power normalised approximated to dotted

line

From Figure 5, the maximum power generated reached at

12:00 noon. The power generated increased gradually from Fig. 7. Integration Calculation to calculate area under
graph
08.00am and reach maximum power generated at 12.00

noon then decrease gradually until For example, in the case of area under the function f(a), the

06.00 integration follows as:

pm. ( ) = 10 .67 0.57x – 4.26
7.5
b) Analytical Estimation of Energy Generation
= 29.8 ℎ
Figure 6 shows the plot that is segmented into a few
And the rest of the function give the value of ( ) =
separation time slots in order to find the area under the plot
460.8 ℎ, ( ) = 420 ℎ, ( ) = 171.2 ℎ,
for each segment and to sum up each areas to find the total
( ) = 310 ℎ and ( ) = 233.55 ℎ
energy generated for one day. Such mathematical
The techniques of working out the total energy generated
calculation is produced as the following the mathematical
from PV-solar at have got a close resemblance with
calculation area and calculated as follows:
mismatch attributed possibly to the difference in estimating
Area (a) = 1 2.33 1 = 1.17 ℎ
2 the slopes, y-intercepts or limits of integration. The total
1
Area (b) = 2 2 1.5 = 1.5 ℎ energy generated in the latter case is 23.57kWh. From both

Area (c) = 2 1.5 = 3 ℎ of the results, certain considerations have to be taken into

Area (d) = 2 3.8 = 7.6 ℎ account such that the area is also included the one that the

Area (e) = 2 3.2 = 6.4 ℎ power generation has loss power. As can be seen from the

Area (f) = 1 2 2.5 = 2.5 ℎ Figure 4, the power generated is considered intermittent that
2
like at 1020am to 1100am the power is loss. This situation

may be due to the cloudy weather that block the PV and

cause the power loss. In order to overcome this problem, it

is suggested that the use of ESS will recover the power loss.

However, one consideration shall be taken like the power
loss due to voltage drop from the ESS‟s switching to the DC

bus need to be overcome by using the ultra-capacitor that

need to be done further.

Fig. 6. Segmentation for calculation area

Resulting thus into total area, Total (a) (f)= 1 + 1.5 + 3 +7.6 +
6.4 + 2.5 = 22.17 ℎ

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Analytical Modelling of Premises-Specific Solar-Energy Estimation

IV. CONCLUSION 14. X. Tang, X. Hu, N. Li, W. Deng, and G. Zhang, “A Novel Frequency

From the results and discussion, the power generated from and Voltage Control Method for Islanded Microgrid Based on Multi-
the PV will be a benefit to the community where the energy Storages,” IEEE Trans. Smart Grid, vol. 7, no. 1, pp. 410–419,
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and while the PV area is large this will make the one local Jan. 2016.
spot for the microgrid and connected to the nearest village. 15. A. Urtasun, E. L. Barrios, P. Sanchis, and L. Marroyo, “Frequency-
In the islanded mode, the PV-farm will be adequate to
supply the electrical energy to one village, and the surplus Based Energy-Management Strategy for Stand-Alone Systems With
may be connected to the national grid for meeting the load Distributed Battery Storage,” IEEE Trans. Power Electron., vol. 30,
demand of a nearby locality. The two analytical approaches no. 9, pp. 4794–4808, 2015.
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System source have produced amounts of energy over the Meeting Peak Hours Demand,” in 5th IET International Conference
same duration two amounts differing by 6.3 % inaccuracy
could be attributed to parametric values, which could not be on Clean Energy and Technology (CEAT2018), 2018, pp. 69 (4 pp.)-
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approaches. Furthermore, the results of this work will be 69 (4 pp.).
used in a subsequent venture for the power flow for
addressing the microgrid supply availability concern.

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and Wireless Droop Control for Distributed Energy Storage Units in
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vol. 32, no. 1, pp. 736–751, Jan. 2017.

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Assessment of Friction Stir Welding on
Aluminium 3D Printing Materials

S.S.S. Abu Bakar, S. Sharif, Mohd Faridh

 five times stronger compare to previous manufacturing
Abstract: This review paper will discuss about the joining process. This project ended up saving about $3 million per
aircraft, per year [4].
process of Aluminium 3D printing materials by using friction stir AM process are considered as the most promising technique
welding process. Currently, the studies on the joining of 3D to fabricate biomaterial such as Ti-6Al-4V alloy for medical
printing materials by friction stir welding are very limited. applications. The process have also resolve several problem
Through this review, the joining materials characteristics such as in the manufacturing of porous and unitised components, for
weld efficiency, hardness and microstructure after friction stir instance improving the compatibility of implants and human
welding process will be discussed to identify the behavior of weld tissue. The prime advantage of AM is the capability to
joint materials. Understanding the friction stir welding process on customized fabricate biomaterial alloy implants to meet
3D printing materials is importance in order to support the future individual patient requirement, and manufacture net-shape
advancement of 3D printing technology in terms of 3D printing metallic biomaterials [9].
part repairing activity and the secondary process such as the Nowadays, the demand of 3D printing keep on increasing in
joining of 3D printing parts. In this paper, the fundamental order to fulfill the demands in producing parts with complex
concept of friction stir welding and powder bed fusion 3D printing geometry at a lower development cost. The increasing
is discussed. At the end of the review, the summary of friction stir demands 3D printing parts in industry would eventually lead
welding process on Aluminium 3D printing materials concluded to the 3D printed parts repairing activity and secondary
that the joining process is feasible to weld the materials with joint process such as joining, foaming and cutting. This secondary
efficiency 83.3% and modify the base material characteristic of process need to be developed in order to support the growth of
the 3D printing materials. the 3D printing application in the future.

Keyword: FSW, EBM, SLM, DMLS, 3D Printing. II. FRICTION STIR WELDING

I. INTRODUCTION FSW process is known to be a robust process and
technique in welding technology for decade. This
3D printing metal is one of the Additive Manufacturing advancement has given the opportunities to the industries to
(AM) process which has been used in many industries such produce superior welds, improved reliability and increased
as automotive [1]–[3], aerospace [4]–[6] and biomedical productivity in joining process technology [10]. FSW has
[7]–[9]. In automotive industries, the demand to reduce the been patent in United State in 24 October 1995 with patent
carbon emission and at the same time improve the number 5460317. This process initially invented by WM
performance and safety of the car inevitable. Figure 1 Thomas and his team from The Welding Institute (TWI),
clearly shows the usage of the 3D printing parts in Cambridge, United Kingdom [11]. In FSW process, the probe
production in U.S and it is predicted to increase from below which is harder than the workpiece is used to weld the
5,000 to 100,000 between years 2015 until 2035. Currently, workpiece together. The probe is allowed to rotate at certain
3D printing technology is used primarily for rapid speed and force into the workpiece joint whereby frictional
prototyping of prototype parts. Apparently, the application heat is generated as the probe enters the workpiece. The
of the technology would increase if the cycle time and heated workpiece material around the probe becomes
equipment cost could be reduced [1]. plasticized and removing the probe allows the plasticized
In aerospace industries, General Electric (GE) has moving region to solidify and joining the workpiece together [11].
forward by investing in 3D printing technology by open new In order to produce a sound and defect-free weld using FSW,
facilities in Chakan, India to focus on flexibility in part the probe geometry design is an important factor besides the
design and production technique. The new fuel nozzle in a FSW process parameters. These parameter setups include
GE jet engine has used 3D printing technology for their next rotation of the probe (in rev/min), travers speed, spindle tilt
generation of LEAP engine. The result from the application angle, and target depth as shown in Figure 2 [12]. FSW
of this new technology, the company can reduce the number process parameters are significant factors which affect the
of the production process, the part become 25% lighter and heat generation, material deformation, process effectiveness,
welding penetration, product quality as well as productivity
Revised Manuscript Received on November 19, 2019 [13].
* Correspondence Author

Shaik Syahman B. Shaik Abu Bakar*, Faculty of Mechanical
Engineering, Universiti Teknologi Malaysia, Johor Darul Takzim, Malaysia.
Email: [email protected]

Prof. Dr. Safian B. Sharif, Faculty of Mechanical Engineering,
Universiti Teknologi Malaysia, Johor Darul Takzim, Malaysia. Email:
[email protected]

Dr. Mohd Faridh B. Ahmad Zaharuddin, Faculty of Mechanical
Engineering, Universiti Teknologi Malaysia, Johor Darul Takzim, Malaysia.
Email: [email protected]

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Evaluation of Friction Stir Welding on Aluminium 3D Printing Materials

Figure 1. Automotive Emerging Manufacturing Processes and Enablers for Growth, 2015 to 2035 in United State [1].

Figure 2: Schematic drawing of friction stir welding

In FSW process, tool or probe rotates and slowly III. METAL 3D PRINTING TECHNOLOGY
plunged into the workpiece at joining line, until the tool
shoulder firmly in contact with the workpiece surface under Metal 3D printing technology is one of additive
applied load. The frictional heat is generated from the manufacturing (AM) processes that can be categorised under
friction area between the tool shoulder, probe and the powder bed fusion 3D printing family. Generally, there
workpiece. The heat generated at the tool shoulder is higher are three types of metal 3D printing technology namely;
compared to the heat generated at the probe surface. Once Electron Beam Melting (EBM), Selective Laser Melting
the workpiece material plactized or semi melted, the (SLM) and Direct Metal Laser Sintering (DMLS) [16].
material experienced severe plastic deformation due to the In EBM process, the parts was produced by melting and
localised heat generated. At the same instance, the solidifying the metal powder on layer-by-layer basis; just like
plasticized material flow from the leading face of the probe the other version of powder bed fusion technologies. The
to the trailing face, where it is forged into the joint [14]. thermal energy used to melt the powder is converted from the
Material flow behaviour during FSW process is a very kinetic energy to thermal energy when the high-speed
complex phenomena and very much poorly understood at electron strikes the metal powder. Due to that, the metal
this moment. The flow characteristic of FSW process has powder temperature would rise to above the melting point and
been suggested as an in-situ extrusion process by some rapidly liquefy the metal powder. EBM process runs under
researchers [15]. The occurrence of stirring and mixing of vacuum environment in order to prevent energy loss and to
weld material only happen at the surface layer of the weld; support the processing of reactive metal alloys such as
adjacent to the rotating shoulder of the probe [12]. titanium [17].

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Another method of 3D Metal printing technology is SLM IV. FRICTION STIR WELDING OF METAL 3D
technology that was invented by Fraunhofer ILT in mid PRINTING
1990s. In this technology, the metal powder is heated up using
laser beam until it is fully melted. The molten metal powder Zhenglin and team from Singapore has conducted a research
would fuse together with the layer below. During the process, of FSW on SLM material in 2018 [21], [22]. The research
inert gas such as argon or nitrogen is used to prevent the melt used a blended metal powder of aluminium powder
pool oxidation and assist in removing metal vapour. The AlSi10Mg and 2% of nano-sized alumina (nAl2O3). The
process which is illustrated in Figure 3, involves a very FSW process was run by using robotic FSW to perform the
complex parameter in order to produces full dense, welding with butt join configuration on 10 mm thickness
metallurgical sound parts with minimal internal stress. material. The geometry of FSW tool was 15 mm diameter
Among the important parameters involved are laser power, with conical pin diameter 6.5 mm and 7 mm respectively. The
scan speed, hatch spacing, powder particle size morphology, FSW parameter used in this study is tabulated in Table 1.
distribution, layer thickness, and scan strategy [18]. In this study, the SLM part had been successfully joined by
FSW and their weldability, mechanical behaviour and
Figure 3: Schematics of the SLM process [18]. microstructure evolution were investigated. The welded SLM
part result was comparable to FSW of wrought AA6061
One of the most effective 3D metal printing technologies is sheets and FSW fragmented and homogeneously dispersed in
DMLS, where the related patent for the field of weld region. Result from the tensile test for SLM part shows
laser-sintering was acquired by EOS in 1997 from 3D the highest weld efficiency is 83.3% and the lowest is 67% as
Systems [19]. In general, the processes between DMLS and shown in
SLM are quite similar in which the parts are developed Tabale From the FSW experiment result on mechanical and
layer-by-layer by using the laser beam as an energy source to microstructural behaviour for AA2219-O and AA7475-T761 alloy,
heat the metal powder [16]. However, unlike SLM process, the researcher found weld efficiency for both materials is 97% and
DMLS does not melt the metal powder completely in order 70% respectively [23]. Meanwhile, the experiment from others
to fuse the metal powder particle together. Instead, the metal researcher for AA6082-T6 and AZ91 Mg alloy result show the weld
powder is sintered by laser to fuse it [20]. Since the sintering efficiency is 72% and 75% respectively as shown in
process occurred at a lower temperature as to compare to
fully melting the metal powder, the laser power usage for [24].
DMLS is lesser than the SLM process. Table 1: Parameter used in Zhenglin study

Process Rotation Traverse Tilt angle, Downward
parameter speed, RS speed, TS TA (O) force (kN)

FSW with (rpm) (mm/s) 4.5 3.5 – 4.5
high heat
input 1200 1 4.5 3.5 – 4.5

FSW with 600 1
low heat
input

Figure 4: Comparison of weld efficiency for 3D printing materials, aluminium and magnesium alloy.

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Evaluation of Friction Stir Welding on Aluminium 3D Printing Materials

From Zhenglin observation, the size of the grain increased macrostructure in welding area compared to SLM part

with the use of high tool rotational speed. However, the fine received with 9% porosity and the hardness and tensile

grains were observed in the nugget zone due to the dynamic strength of weld was reduced due to the precipitation of Si.

recrystallization process. A higher amount of Si was found in Besides a higher ration of rotational speed to transverse

the advancing side of the welds due to higher temperature speed would also lead to larger grain size and lesser

generated in the area where more Si particles were hardness.

precipitated out. The FSW produced porosity-free

Table 2: Weld Efficiency of SLM joining by using FSW process [22]

Material and Process Weld Efficiency (%)

FSW of SLM AlSi10Mg with low heat input 67

FSW of SLM AlSi10Mg with high heat input 67.8

FSW of SLM AlSi10Mg - 2% wt. nAl2O3 with low 83.3
heat input

FSW of SLM AlSi10Mg - 2% wt. nAl2O3 with high 77.1
heat input

Researchers from Italy, Scherillo, Hassanin and team has Figure 5: DMLS Aluminium Specimen after joining with FSW

reported and conducted an experiment to study method [25].

microstructure of FSW of Aluminium fabricate by DMLS Table 3: Vickers Hardness of the different zone of the joint

with same experimental setup [25], [26]. In this research, a 3 of AlSi10Mg DMLS part [26].

mm thickness specimen was fabricated using AlSi10Mg Zone Vickers Hardness (HV)

metal powder (Figure 5). The FSW parameter used for Base Material (BM) 93 ± 3

rotational speed and transverse speed was 800 rpm and 200 Thermal Mechanical Affected 98 ± 1
mm/min. Compared to Zhenglin’s study, the rotational speed Zone (TMAZ) 101 ± 2
Nugget Zone
used was between the ranges of high and low heat input in
Zhenglin’s study. However, the transvers speed in this study Figure 6: Hardness profile of SLM joining by FSW [22].
much higher than the one in Zhenglin’s study. The result from The differences of the hardness trend at nugget zone between
Zhenglin and Scherillo study also happen for the other grades
the study shows that, AlSi10Mg DMLS parts had been of wrought aluminium materials. A Finding from an India
researcher for AA2219-0 and AA7475-T761 similar and
successfully joint with free macroscopic defects and fine dissimilar join, show that the hardness value at the nugget
zone was higher compare to the base material [23]. As
grain homogeneous macrostructure observed within the compare to a finding from Portugal
researcher for AA5083-H111 and
nugget zone. The macro-hardness from Scherillo report in AA6082-T6 joining, the hardness

this study also shows that the hardness at nugget zone is

higher than the base material hardness (Table 3). This finding
contradicts to the result from Zhenglin’s study. In which the

hardness value within nugget zone is lower than the base

material hardness (Figure 6). However, there is no result
regarding the micro-hardness from Hassanin’s report.

Researchers from Italy, Scherillo, Hassanin and team has

reported and conducted an experiment to study

microstructure of FSW of Aluminium fabricate by DMLS

with same experimental setup [25], [26]. In this research, a 3

mm thickness specimen was fabricated using AlSi10Mg

metal powder (Figure 5). The FSW parameter used for

rotational speed and transverse speed was 800 rpm and 200
mm/min. Compared to Zhenglin’s study, the rotational speed

used was between the ranges of high and low heat input in
Zhenglin’s study. However, the transvers speed in this study
much higher than the one in Zhenglin’s study. The result from

the study shows that, AlSi10Mg DMLS parts had been

successfully joint with free macroscopic defects and fine

grain homogeneous macrostructure observed within the

nugget zone. The macro-hardness from Scherillo report in

this study also shows that the hardness at nugget zone is

higher than the base material hardness (Table 3). This finding
contradicts to the result from Zhenglin’s study. In which the

hardness value within nugget zone is lower than the base

material hardness (Figure 6). However, there is no result
regarding the micro-hardness from Hassanin’s report.

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trend shows no significant changes for soft tamper material, macrostructure shape with onion ring shape at AS for both
figures.
but the hardness is reduced at nugget zone for base material
AS RS
with higher hardness value due to dissolution of the hardening
Figure 7: Macrograph of the DMLS parts joint by FSW with
precipitates [27]. highlighted the different zones [26].

From Table 4, the trend of hardness at nugget show all the Figure 8: Macrograph of 5A06 aluminium alloy joint by FSW
with highlighted the different zone [28]
SLM material hardness at nugget zone was reduce while for
V. CONCLUSION
DMLS material was increase. The difference in trend of From the research, FSW is proven able to be used as one of
the methods to join the metal 3D printing materials. By using
hardness in nugget zone also can be observe in FSW for proper FSW tools and correct parameter setting a sound and
defect-free weld can be produce in order to joint the metal 3D
wrought aluminium alloy. Although the hardness trend at printing materials. Besides, the FSW tools must be harder
than the materials that need to weld. The most important
FSW nugget zone was different from those reported by parameters in FSW are the rotation of probe, travers speed,
spindle tilt angle and target depth.
various researchers, the similar finding from the report shows Although EBM, SLM and DMLS have been categorized
under powder bed fusion, only SLM and DMLS had been
that the grain size modification had occurred at the FSW weld reviewed for joining by FSW. This is due to lack of
information on EBM joining process by FSW. The weld joint
zone. efficiency of FSW on the 3D printing metal can reach up to
83.3% compared to its base materials strength. Meanwhile,
Table 4: Comparison of FSW hardness at nugget zone from the micro-hardness trends cannot be concluded due to the
various study. inconsistent result. However, most of the researcher found
that FSW process modified the microstructure of the
Materials Base Hardnes Trend Referance materials by refining the grain structure. The macrograph of
FSW 3D printed metal and other aluminium alloys show
Material at weld similar welding zone shape with AS of the weld zone different
from the RS.
Hardnes, zone, At this moment, the published research paper for FSW on 3D
printing materials are very limited. Due to this matter, the
Hv Hv information related to FSW on metal 3D printing material is
difficult to be compared and studied. It is hoped that, this
SLM 139 68 Reduce [22] present summary could help other FSW researchers to better OR
understand the joining process of metal 3D printing materials
AlSi10Mg using the FSW process.

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Evaluation of Friction Stir Welding on Aluminium 3D Printing Materials

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The Application of Taguchi Method in
Optimizing Fabrication of Composite Panel for

Particleboard

M.N.M.Baharuddin, Norazwani Muhammad Zain, Eida Nadirah Roslin, W. S. W. Harun

 process and UTM testing used. The DOE was design by
Abstract: This paper titled The Taguchi Method application Taguchi method [3] while the analysis result of data was
carried out by using ANOVA through Minitab 17 software.
for mechanical properties in the making of particleboard was one
by considering the Modulus of Elasticity (MOE) and Modulus of II. MATERIAL AND METHOD
Rupture (MOR) as a testing parameter. This research was done by
using combination of dust wood and fruit from Acacia itself as A. Materials
main materials. It was mixed with Polyurethane (PU) as a resin The choice of Acacia tree as a fiber material in this
and Paraffin Wax (PW) as a filler with specific values. This study
mainly uses Hot Press Machine (HPM) and the Universal Tensile exploration is to lessen the forestation exercises. Right now,
Machine (UTM) to produce and test specimens. The TGA analysis Acacia trees are seen uncontrollably developing in Peninsular
was used to prove the indicator of temperature before the process Malaysia however left relinquished. By utilizing the waste,
of the specimen began. Meanwhile the SEM and EDX testing were for example, the parts of Acacia tree, it will build the
used to identify spectrum of chemical content in the specimen estimation of this species and evade the air contamination due
after the testing process was done. The Taguchi Method is used to to open consuming exercises [4]. Every one of the segments in
create the design of experiment (DOE) table that contains the Table I is the primary factors really taking shape of
optimized parameter of experimental results. While to foresee the molecule board.
degree of centrality tests that add to the solidarity of the quality is
finished by ANOVA with Minitab 17 programming. The result Table I: List of materials used (Particleboard)
will be compared with the Japanese Industry Standard (JIS) for
MOE and MOR testing. From the research, the optimized formula List of components Types of item used
was A3B3 specimen. The results obtained for MOE was 5134
(MPa) for Modulus Young and the result of MOR was 21.9 (MPa) Fiber/Particle Acacia tree and Fruit of Acacia
for Flexural Strength.
Resins Polyurethane (PU) adhesive
Keywords: Homogeneous particle board, palm oil fiber
Filler Paraffin Wax (PW)
I. INTRODUCTION
B. The Pre-Treatment Process
Nowadays, the manufacturing industries are looking The foods grown from the ground wood pieces of Acacia

forward to produce high quality product with minimal cost tree were washed with faucet water to expel any unused, trash
[1]. to get a product with these characteristics, these from cutting procedure, earth and undesired substances. After
manufacturers must have the best formula as a reference [2] in that it was dried at an atmospheric temperature range between
the making of the product. The formula must have a good 28 °C to 300C prior to next treatment process. After that it was
value of modulus young and flexural strength. At the same treated with sodium hydroxide (NaOH) solution at 8% by
time, the selected of material sizes, types of resin, additive as volume of clean water [5]. This process was continued by
a filler, parameters and indicators must be accurate in order to soaking these materials in NaOH solution for 3 hours at room
avoid wastage which can increase the cost of money, time and temperature. After that it was washed twice or more with
energy to the industry itself. Therefore, the purpose of this distilled water to allow absorbed alkali to leach from the
study is to determine the optimum value in the making of material content. The fruit and the branches of Acacia tree
particleboard by using the Taguchi Method application. The were dried in an oven maintained at 80°C with ±50C [1]. This
appropriate parameters also will be produced for HPM process was kept ongoing until the Moisture Content (MC) of
the material achieved % to 13% [6] of the temperature value
Revised Manuscript Received on November 19, 2019 prospect as what JIS needs before proceeding to the next
M.N.M.Baharuddin, Kolej Kemahiran Tinggi MARA, Petaling Jaya process.

No. 12 Jalan Templer 46000 Petaling Jaya, Selangor, Malaysia. In other literature, it was said this procedure is done to lose
Norazwani Muhammad Zain, Universiti Kuala Lumpur Malaysia the cellulose structure, producing a halfway structure being
changed over to a carbonized fiber empowering simpler
France Institute, 43650 Bandar Baru Bangi, Selangor, Malaysia assimilation of the pitches for the
(Corresponding Author: [email protected] ) following procedure. The
absorption shown that the NaOH
Eida Nadirah Roslin, Universiti Kuala Lumpur Malaysia France
Institute, 43650 Bandar Baru Bangi, Selangor, Malaysia.

W. S. W. Harun, Faculty of Mechanical Engineering, Universiti
Malaysia Pahang, 26600 Pekan, Pahang, Malaysia.

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The Application of Taguchi Method in Optimizing Fabrication of Composite Panel for Particleboard

treatment played a positive role in forming of specimen and decompose after 237oC and the PU starts to cure after 120oC
reaction of resins process [7]. During the process, the dried of [12].
products of the soil parts of Acacia tree were put away in a
fixed plastic pack to stay away from climatic dampness At the same time, certain polymeric of waxes such as PW
tainting preceding the granulating procedure to get the residue may require over the temperature range of 0-130 °C to
from both of material. This is to control the MC of the analyze. Some of them also required a higher upper
material. temperature limit (150°C -170°C), this is in order to obtain a
C. Preparation of Acacia Sawdust (Fruit and branches) complete melting profile [13]. Because of that the value of
120oC was the optimum temperature in the making of
The branches and fruit of Acacia tree as shown in Fig. 1 particleboard by considering the PU peak curing temperature
was grinded using grinding ball machine type Pulverisette 7 at 120oC, the material started to decompose and the higher
from FRITSCH Model to get uniform size of particle. The upper temperature limit of PW. Table III shows the
sizes of particles are in the range of 4mm>x>2mm [9]. After dimensions of specimen and their types of testing [7].
sieving process, the particles were dried once again in an oven
for 48 hours at 800C±50C to obtain between 5% to 13% of Table III: Dimension of Particleboard
moisture content [7] prior to the fabrication process [2].
Types of Testing Dimension

MOR and MOE 200mm x 50mm x 10mm

The formulations of particleboard are indicated in Table IV.

The PU adhesive was prepared by reacting the isocyanate and

palm kernel oil based polyol with a ratio of 1:1, 1:1.5 and 1:2.

Fig 1: Acacia Tree and Fruit of Acacia Meanwhile, the weight of combination between dust wood of

D. Production of Particleboards Acacia and the fruit of Acacia was calculated by using (1):

In the manufacturing of particleboard, polyurethane (PU) ρ = m/ν (1)
adhesive was used as main resin. Three different sizes of
specimen were used and the target density (750kg/m3) was set The particles (Acacia and the fruit) were blended with PU
at medium density (400 kg/m3 to 900 kg/m3) range according
to JIS [7]. adhesive and filler (PW) and the mixture was stirred until it

The percentage of filler was fixed to 0%, 10% and 20%. well blended by using the optimization formula from table
The combination of material between dust of fruit and dust of
Acacia tree was fixed to ratio 50:50. These conditions are DOE created earlier by Taguchi Method. Then the mixture
believed to be capable in increasing the mechanical properties
of particleboard [10]. The preparation of the board specimens was put into the mold and pressed using a Hot Press Machine
in this research depended on the required weight fraction and for 5 minutes [2] at 1600C. Nine specimens for each MOE
sieving size. The processing parameters used in the
particleboards production are shown in Table II. and MOR were created using mixed hardwood species by

cutting them into specific structure according to JIS. The
specimens‟ density ranges from 400 kg/m3 to 900 kg/m3 were

processed into standard sizes, 200mm × 50mm × 10mm (2 × 2

× 30 inches). The modulus of rupture (MOR) was calculated

by using (2):

(2)

Table II: Parameters for particleboard production

Parameter Details where P = applied load (N), L = span (mm), b = width (mm) of
the specimen and d = depth (mm) of the specimen. Modulus
Target density (kg/m3) 750 of elasticity (MOE) was calculated by using (3):

Pressure Time (min) 5 (3)

Pressure (bar) 160 where P = applied load at the limit of proportionality (N), L =
Temperature (0C) 120 span (mm), Δ‟ = deflection at the limit of proportionality
(mm), b = width (mm) of the specimen and d = depth (mm) of
The desired density for the research was 750 kg/m3. It was the specimen. The local modulus of elasticity was calculated
in the range of medium density (400 kg/m3 to 900 kg/m3) by by using (4):
following the Japanese Industry Standard (JIS). This selection
of range density was believed can reduce the particleboard (4)
manufacturing cost but still can produce the strongest
particleboard. The Pressure of time in the research was 5 where a = distance (mm) between a loading point and the
minute [11]. The pressure was 160 (bar) and it was set by nearest support, l1 = gauge length (mm), I = second moment
referring to the previous experiment and others researcher [2] of area (mm4), ΔF = increment of
[11]. Figure 6 shows the TGA result that the material starts to load (N) and Δw = increment of
deformation (mm) corresponding

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to ΔF. The deflection for local MOE was measured on one Meanwhile, the ANOVA with Minitab 17 software was set
side of the specimen. The modulus of elasticity was calculated with Main Effects Plots (MEP) to get the multi response result
by using (5): to obtain the optimization parameter. Here, the mean data
were plotted for each level of one or more factors to examine
(5) how the factors influence the response. The Fig. 2 shows the
table of MEP.
where a = distance (mm) between a loading point and the
nearest support, l = bending span (mm), b = width (mm) of the
specimen, h = depth (mm) of the specimen, ΔF = increment of
load (N) and Δw = increment of deformation corresponding to
ΔF (mm). The modulus of rupture (MOR) was calculated by
using (6):

(6)

where Fmax = maximum load (N), a = distance (mm) between Fig 2: Main Effects Plots (MEP)
an inner load point and the nearest support and W = section
modulus (mm3). A small portion was cut from every III. RESULT AND DISCUSSION
specimen for the determination of wood density. The density A. The Taguchi Method Analysis
of specimen at test was calculated from the equation (7) where
ρtest = density (kg/m3) at test, m = mass (kg) at test and V = Table IV shows that Taguchi Method software only
volume (mm3) at test. presents two factors set when in fact this research propose
four factors. They are size of material, Polyol, Isocyanate and
(7) PW. However, based on the result from the previous research,
[9] the best size of material in the making of the particleboard
E. Design of Experiment (DOE) and Main Effects Plots was 2mm<x<4mm. The same goes to the Polyol, it was set as
(MEP) a constant value. In this research the weight of 45g based on
the ratio (Polyol: Isocyanate) 1:1, 1:5 and 1:2 Became the
During the research, the Taguchi Method software was main reference. Due to this, there are only two factors left to
used to create a Design of Experiment (DOE) table. be put into DOE in the Taguchi Method. They are Isocyanate
Meanwhile to predict the level of significance tests that and PW.
contribute to the unity of the strength is done by ANOVA with
Minitab 17 software. The Taguchi method used 3 level Table V: DOE and Result of Response
designs for table type of design.
Nine optimization formulas were created by DOE formula
There are two (2) contributing factors in this research, and were tested to the two responses, MOE and MOR result
which are Isocyanine and PW. Meanwhile the display only. The table below shows the result of the DOE process.
available for Taguchi Designs (With number factor) for single B. The Result of MOE
level design was set for L9 and 3-level with indicator 2-4.
Here, the Taguchi Design column was run at L9 and the 3ʌ2. Table VI shows the 9 results of specimen for modulus
After that the Taguchi Design factor column was assign with young [MPa] during the Modulus of Elasticity (MOE) testing.
name of factor as A and B (an Isocyanine and PW) and the The lower value was specimen no.1 with 3761.816 MPa as the
level of level value column was set name as 1,2 and 3 (refer to result. Meanwhile the higher value was the specimen no.9
the picture of flow chart). with 6572.995 MPa as the result. The mean value for 9
specimens was 4982.002 MPa and the maximum load for
The DOE from Taguchi Method is important to get the mean [kN] was 1.658. This result proved that the JIS
Optimization Formula. The table below is the DOE table requirements for MOE testing have been successfully
created by using Taguchi Method software. achieved [7].

Table IV : Design of Experiment
(DOE)

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The Application of Taguchi Method in Optimizing Fabrication of Composite Panel for Particleboard

Table VI : Result MOE by Using Universal Tensile Machine particleboard was below the 237oC. A temperature higher
(UTM) than that will reduce the weight of the specimen and
significantly affect the density and strength of the specimen
[2].

C. The Result of MOR Fig 3: TGA Result for A3B3

Table VII describes the details in procedure B with 160 E. SEM and EDX Specimen Testing Result
mm support span. The span-to-depth ratio was 16:1 and the
support radii (mm) was 3:2. It was same goes to the Loading The SEM is the process to identify the molecule of the
radius (mm) with ration 3:2. The rate 1 with 42.67000 specimen. Meanwhile the EDX is the process to identify the
mm/min was use as a speed process during the testing. All the chemical content of the specimen. Fig 4 shows the spectrum
indicator comply with the ASTM D 790-10 (Standard Test of Nitrogen, Oxygen, Hydrogen and Carbon in the specimen.
Method for Flexural Properties of Dust Wood and Fruit of A composite must possess a spectrum of Oxygen and Carbon
Acacia). content. The figure proves that the specimen is indeed a
composite specimen as it shows the spectrum of Oxygen and
Table VII: Basic parameter for MOR testing Carbon it contains [12]. At the same time, the Nitrogen
spectrum proves that element of PU exists in the specimen.
However, due to its characteristic of being light molecule,
Hydrogen spectrum does not appear on the result screen.

Table VIII shows the result of MOR by using the Universal Fig 4: Synthesis of Polyurethane from a di isocyanides
Tensile Machine (UTM). The 9 specimens were tested. and a diol
Specimen no. 5 shows the lowest result with 8.32 MPa of
flexural strength. It gives out 0.45197% of Flexural Strain. Fig 5 shows he picture of the specimen by using the SEM. It
Meanwhile the higher result was specimen no 9 with 21.9 has gone through a zooming of 1756 times. The result shows
MPa. It gives out 0.76244 % of Flexural Strain. The mean the specimen has spectrum of Carbon, Nitrogen and Oxygen.
result of the test was 18.1 MPa with 0.70396 % of Flexural The value of the Carbon was 64.38%, Nitrogen 1.91% and
Strain. The Standard Deviation was 5.2 MPa and the Flexural Oxygen was 33.71%. These molecular contents show that this
Strain was 0.16%. research is a polymer research with the presence of Carbon,
Nitrogen and Oxygen. The high Carbon content proves that
Table VIII: Result MOR by Using Universal Tensile Machine this particleboard specimen has a great potential to produce
(UTM) high quality furniture‟s.

D. TGA Specimen Testing Result

The TGA testing was done by using the specimen with
A3B3 formula. During this experiment, the range of
temperature was set to the 900oC. It was dynamic scan with 10
oC per minute as a setting. The graph shows that the specimen
started to decompose at 237°C and reduces at 389°C. The
result concluded the best temperature in the making of the

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Fig 5: SEM and EDX Result IV. CONCLUSION AND SUGGESTION

F. The Taguchi Method Analysis The research and tests conducted has produced an
Taguchi Method applies he indicator “Bigger is better” by optimization formula, the A3B3 formula. his formula was the
best combination of all elements (material, resins, hardener
using Analyze Taguchi Design to analyze the MOE and MOR and the filler) in the making of homogenous particleboard for
result. Fig 6 and Fig 7 respectively show the “Main Effects manufacturing industries. This result is a well approved
Plot for Means” and “Main Effects Plot for SN Ratios” with decision from the analysis done using the Taguchi Method
A3B3 as the best finding for MOE and MOR testing. This is software through single respond analysis for “Bigger is
also used as an indicator to prove that increment in PW and better” and it is supported with ANOVA software showing the
hardener will significantly affect the strength of the material same result. For future research, a run on the conformation
[13]. test (A3B3) will be done to obtain optimization parameter. At
the same time, the SPSS software will be used to produce the
mathematical model and to see the most significant factor in
the research. Three specimens must be produced by using the
Hot Press Machine and it must be tested by going through the
same procedure as the Taguchi Method process. The
specimens also have to be tested by using the TGA, SEM,
EDX and FTIR testing (extra testing procedure). The result
from the conformation test will be the support indicator to
produce the homogenous particleboard from the Acacia
species product in the future.

ACKNOWLEDGMENT

We want to recognize University of Kuala Lumpur for the
momentary research award (str18007). We additionally offer
our thanks to all who had contributed in this examination
including exhortation, works and rule

Fig 6: Graph for Min Fig 7: Graph for SN Ratio REFERENCES

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The Application of Taguchi Method in Optimizing Fabrication of Composite Panel for Particleboard

11. Mohammad Dahmardeh Ghalehno*1, MortezaNazerian1, Ali characterization of porous metallic biomaterials, Bio-functionalizing
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Metallurgy and Particulate Materials Association (MPM2A), Japan Society
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Instrumental Analysis. Institute for Polymer Science Department of

Chemistry.

AUTHORS PROFILE

Mohd Nazif Mohd Baharuddin was born in Malaysia in
1978. He received the B.E with honor from Malaysia
Nasional University (UKM) and M.E degrees from Tun
Hussein Onn University (UTHM), Johor, Malaysia, in
2000 and 2013, respectively. In 2016 he continues study
in PhD degree at Kuala Lumpur University as a part time
student. He joined technical and vocational training department in People's
Trust Council, commonly abbreviated as MARA (Malaysian government
agency) in 2001. Since that time, his duty as Vocational Trainer Offices
(VTO) lectured more focus in mechanical, Automotive and Oil and Gases
courses. Now his duty is as a Director of KKTM Petaling Jaya .Mr. Mohd
Nazif is a member of the Board of Engineers Malaysia (BEM) and Malaysia
Board of Technologies (MBOT).

Norazwani Muhammad Zain is a Senior Lecturer and
Head of Section (Postgraduate) of the Universiti Kuala
Lumpur Malaysia France Institute (UniKL MFI) since
2005. She is also a leader of Materials Sub-Cluster for
Advanced Manufacturing, Mechanical and Innovation
Research (AMMIR) at UniKL MFI. She also an active
research member of Frontier Materials Research Group (FMRG) located at
Universiti Sains Islam Malaysia (USIM). In 2018, she has been appointed a
Visiting Lecturer at Polytechnic University of Catalonia (UPC), Spain and
Institute of Technology Bandung (ITB), Indonesia. She received a B. Sc.
(Hons) in Material Science from Universiti Kebangsaan Malaysia in 2001,
and M. Tech in Material Science from Universiti Malaya in 2004. She then
obtained her Ph.D. in Material Science from Universiti Kebangsaan
Malaysia in 2014. Her research interests include adhesive bonding, weld
bonding, coatings and natural composites. She received several international
and local research grants from 2015 – 2019. She also actively involves in
professional bodies such as Malaysia Board of Technologies (MBOT),
Malaysian Society for Engineering & Technology (MySET), and the Plastics
and Rubber Institute Malaysia.

Dr Eida Nadirah Roslin is a Senior Lecturer at
Universiti Kuala Lumpur, Malaysia France Institute. She
obtained her Bach. Of Engineering in Manufacturing
from International Islamic University Malaysia, Master of
Engineering in Manufacturing System from Universiti
Putra Malaysia and PhD in Engineering (Manufacturing
System) from University of Malaya, Malaysia. She is currently a Research
Principle for Advanced Manufacturing, Mechanical, and Innovation
Research Lab. Her research interests include Manufacturing System,
Operation Management, Lean System, Sustainable Engineering and
Renewable System.

Wan Sharuzi Wan Harun is a Senior Lecturer and Head
of Program (Biomechanics) of the Faculty of Mechanical
Engineering at Universiti Malaysia Pahang, where he has
been since 2006. He also currently serves as a researcher,
a consultant, and a technical expert advisor for Additive
Manufacturing Research & Innovative Centre (AMRIC) and Orthopedic
Research Laboratory (ORL) located at International Islamic University of
Malaysia. During 2010-2011 he was a Visiting Researcher at the Material
Processing Laboratory at Kyushu University, Japan. He received a B. Eng.
(Hons) from Universiti Malaysia Sarawak in 2004, and a MEng. From
Malaysia Technological University. He received his Ph.D. in Mechanical
Engineering (Powder Metallurgy) from the Kyushu University in 2013.
From 2004 to 2006 he worked at Agilent Technologies in Malaysia,
eventually as an Industrial Engineer.
His research interests centre on promoting green manufacturing practices
through powder metallurgy field, principally through the synthesis and

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Optimization of Foam-Filled Square
Thin-Walled Aluminium Structures

Nurul Izzah Ab Rahim, Salwani MS

 research papers that compared the performance of structures
Abstract. Crash box are the structural part designed to absorb in different cross-sections such as circle [3], square [4] and
polygonal [5] under different impacting velocities.
energy during crash and minimize the injury to passengers. Haorongbam et al. found that energy absorption capacity of
Various design of energy absorbers has been introduced to all the double hat-section is better than the single
unleash design with the best crashworthiness behavior. hat-section[6]. Moreover, the carbon fiber reinforced plastics
Foam-filled structures are one of the promising designs. In this (CFRP) has gain much attention due to remarkable structure
study, foam-filled structure was investigated to increase the and performance.[7]
energy absorption capability and reduce the initial peak force
simultaneously. Since most foam-filled structures tend to absorb Instead of varies in cross-section, a few design have been
more energy with high peak force, optimization of the energy introduced to enchance the performance of crashworthiness
absorbers is significant in obtaining the optimum design. structure such as multi-cells structures, functionally graded
Response surface methodology (RSM) has been dominant thickness structures and corrugated tubes [8]. Alavi Nia and
technique in crashworthiness optimization mainly because of it Parsapour [9] compared experimental and simulation results
provides efficient and accurate solution. This paper focused on of multi-cell with triangular, square, hexagonal and octagonal
the optimization foam-filled columns with respect to thickness of sections. Results shown that all the multi-cell had greater
the tube and length of foam to enhance energy absorptions and specific energy absorption (SEA) in comparison with the
reduce initial peak force. The optimization results suggested by simple structure. Xie et al developed 5 structures with
Design Expert software for impact test is 515.9 J for EA and different arrangement of the interior tube walls and
134.94kN for IPF value with the column thickness of 2.0mm and connectivity with the exterior tube walls [10] and concluded
foam length of 185mm. For quasi-static test, the optimum that the crushing force and energy absorption influenced by
solution value for EA and IPF are 864.5J and 88.33kN the sectional form of the structure. The study was extended by
respectively with column thickness of 1.87mm and foam length of Fang et al [11] by introducing the functionally graded
200mm. thickness to multi-cell tubes. The simulation results shown
that the functionally graded thickness tubes have higher
Keywords : optimization, energy absorption, initial peak force, energy absorption capability than the uniform tubes. Figure 1
foam-filled column shows the design of multi-cell and corrugated tubes
introduced to enhance the energy absorption capability of the
I. INTRODUCTION structure.

Aluminium thin-walled structure has been used as a Fig. 1.Configuration of the (a) functionally graded multi-cell

crash box as it can dissipate energy excellently. This paper tube [11]and (b) the sandwich sinusoidal lateral corrugated tube
was divided into 4 major part. Part 1 gives an overview of the
design of empty and foam-filled structures and the energy [25]
absorption capability of the design. Part 2 describes the
design and experimental procedure, consists of specimen Then An et al [12] found that under axial crushing
preparation and optimization method of foam-filled structure
under quasi-static and dynamic loading. Later, part 3 presents condition, specific energy absorption of functionally lateral
and discusses the experimental results of the structures
together with the optimization results and finally the graded thickness tubes are always greater than those of
conclusion was describing in part 4
uniform tubes. Apart from that, a quasi-static axial crushing
The energy absorption capability must be high and initial
peak force should be sufficiently low and the fluctuation experiments conducted by Zheng et al.[13] has similar
should be in controlled manner to avoid the impact from
causing injury to the passenger[1]. Uma Devi et al have conclusion that laterally variable thickness multi-cell tubes is
conducted a simulation study to find an optimum cross
sectional shape of a crash box to ensure high capability for better compared to the uniform tubes. Later, a study
energy absorption without crash beads [2]. There are few
conducted by Sun et al.[14] proven that tubular structures
Revised Manuscript Received on November 19, 2019
* Correspondence Author with graded thickness was

Nurul Izzah bt Ab Rahim, Fakulti Teknologi Kejuruteraan Mekanikal remarkable compared to uniform
dan Automotif, Universiti Malaysia Pahang, 26600 Pekan, Pahang Darul
Makmur Email: [email protected] counterparts under axial loading.

Salwani binti Mohd Salleh, Fakulti Teknologi Kejuruteraan Mekanikal Besides multi-objective
dan Automotif, Universiti Malaysia Pahang, 26600 Pekan, Pahang Darul
Makmur Email: [email protected]

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Optimization of Foam-Filled Square Thin-Walled Aluminium Structures

optimization shown that graded thickness structure achieves decreased.
high SEA and low initial peak force (IPF). The crushing behavior of polygonal structures were

The study on corrugated tubes demonstrated that the energy optimized using RSM by Liu [29]. Thickness of the tubes and
absorption capacity of structures could be increased by using cross-section edge length were chosen as input factor for the
the corrugation design. Corrugation design is development response of maximum SEA. In other paper, the optimization
folds in rows of wavelike or basically formed into a series of of a square crash box with multi-cell design to maximize the
regular folds that appears like waves[15]. Experimental study energy absorption and minimize the peak force conducted
by Eyvazian et al [16] proven that deformation mode of the using RSM [30]. Several objective functions have been
corrugated metal tubes are more stable and controllable. evaluated including linear, quadratic, cubic, quartic and
Besides, the corrugation has succeeded in reducing the initial quintic polynomial and the quartic polynomial function
peak force of the metal tube. Deng and Liu [17] carried out the produces the best fit RS model. Study conducted by Fang et al
crashworthiness study on sandwich sinusoidal lateral [31] found that response surface methodology (RSM) is
corrugated (SSLC) tubes and optimization showed that the capable in producing fit approximation models for energy
maximum crushing force and SEA can be reduced compared absorption and the suitability of the model can be predicted
to that of the single tubes. The truncated conical sandwich using ANOVA.
shell with corrugated was fabricated and optimized by Yang
et al [18] has shown great potential to be applied as The objective of this study was to optimize foam-filled
crashworthiness structure. Deformation mode of the TCSS structures in term of thickness of the tube and length of foam
shown an additional plastic hinges due to strong interaction to increase energy absorptions and reduce initial peak force.
effect of the face sheet and the core which relates with the This study proposes foam-filled tubes with 5 different
excellent energy absorption capacity configurations of foam length and two different thicknesses of
tube in order to offer better energy absorption and lower
However application of thin-walled structures as crash box initial peak force compared to the full-filled tubes.
have led to existence of undesirable IPF and the fluctuation in Quasi-static and impact test were conducted for all the
force-displacement curve when subjected to non-axial specimen. The experimental data were optimized using
loadings[19]. The instability problem in a thin-walled response surface model to achieve maximum energy
structure has evoked the application of polyurethane as a filler absorption with minimum initial peak force.
in the structural member. Polyurethane are unique polymer
material with wide range of physical and chemical properties II. METHODOLOGY
that is widely used in energy absorption’s application such as The flow of the research works has been simplified in the flow
in passive safety mechanism in automotive industries. It has chart in Figure 2
the ability to absorb energy while deforming due to the
mechanics of cell crushing[20] Polyurethane foam-filled Fig. 2. Methodology flow chart
structure may compensate irregular overall buckling and the
unstable effect during crushing process[21]. Besides,
foam-filled thin-walled tubes were introduced to enhanced the
energy absorption while maintaining the mass of the vehicle.
This is because the foam helps to support the energy
absorption capability of the structure [22]. It was supported
by a study conducted by Hussien et al that found the specific
energy absorption of foam-filled structure was higher
compared to hollow one [1]. Similar results gained by Yan et
al in the study on lateral crushing of polyurethane foam-filled
natural flax fabric reinforced epoxy composite tubes [23].

Hanssen et al [24] has proven that insertion of foam inside
the foam-filled structure significantly increases the energy
absorption capability of the thin-walled column but
concurrently increases the initial peak force. This was
supported by Song et al. [25] that concluded that the energy
absorption of foam-filled structure is higher than the sum of
energy for the foam and the hollow structure individually. The
foam is functioned as an elastic foundation for the tube walls
to minimize the local buckling distance and allow extra
progressive folds to be generated[26]. Furthermore, Yan et al
[27] has proven that foam-filled corrugated sandwich can
increased substantially the mean crushing strength and energy
absorption capacity of the beam. Other than that, this design
has altered the failure mode and increased the bending
resistance of the metallic beams. Similar results obtained by
Mahbod and Asgari [28] shown that foam-filled corrugated
tubes has improved the energy absorption capacity in axial
and oblique loading condition. The study also proven that by
increasing the foam density, the SEA of the tubes has
increased simultaneously while crushing force efficiency

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A. Preparation of specimen accurate solution. Besides, analysis of variance (ANOVA)
can be used to predict model suitability before it can be
Square column with dimension 80mm x 80mm x 200mm implemented in design optimization[31]. As an energy
with 1.4 mm and 2.0mm thickness were prepared as energy absorber, the foam-filled structure is required to absorb
absorber. Both types of these energy absorbers were filled maximum impact energy. Thus, the energy absorption should
with foam that have been prepared and cut into the desired be an objective function and be maximized from the
length. Table 1 represents the configuration of each specimen. optimization perspective. While, the initial peak force of the
Thin-walled square structures were made of aluminium alloy structure is another significant parameter that relates to the
AA6063. The specimens were test under quasi-static and safety of the passenger, which should be minimized.
dynamic loading condition to determine the EA and IPF
achieved by each configuration. The response surface model was formulated based on
historical data method using two levels for two central points
Table- I: Notification of specimen in Design Expert software. This research was focused on two
parameters which is thickness of the thin-walled tube that
Notification Column Foam were 1.4mm and 2.0 mm and length of foam that ranged from
thickness length 185mm to 200mm.

A1.4P0 1.4 No foam Response surface model was conducted to the experimental
data using statistical software named Design-Expert. The
A1.4P185 1.4 185 RSM prepared an effective method of formulating estimated
functions for unknown responses using linear, quadratic, or
A1.4P190 1.4 190 higher-order polynomials. The commonly used response
surface models are those using linear or quadratic
A1.4P195 1.4 195 polynomials.

A1.4P200 1.4 200 Generally, it is a bit challenging to formulate the
mathematical relationship between SEA and IPCF by taking
A2.0P0 2.0 No foam into account the material properties, nonlinearities geometry,
and contact-impact nonlinearities [32]. A few techniques are
A2.0P185 2.0 185 suggested for example the RSM to considered those effects of
suitable parameters in designing energy absorbers [28]. The
A2.0P190 2.0 190 design parameters are stated mathematically as below.

A2.0P195 2.0 195 (1)

B. Index of crashworthiness where p indicates the quantity of basic functions, while is
the unknown coefficient to be measured. The coefficients
The crushing behaviour of the thin-walled square structures
can be analysed regards to various parameter such as the IPF of the polynomial terms can be determine
(initial peak force), MCF (mean crushing force), EA (energy by employing the least-square method,
absorption), and SEA (specific energy absorption). Some of
these indices are described in Table II. (2)

Table- II: Notification of specimen where  is a matrix composed of basic functions
assessed at these M design sampling points and can be
Parameter Symbol Description presented as:

Initial peak IPF relates to the first point at which
force force is highest for first fluctuation
in load-displacement curve

Energy EA area under the force-displacement
absorption curve.

Mean MCF is achieved by dividing the energy
absorption with the displacement
crushing force

Specific SEA energy absorbed per unit mass
energy
absorption

C. Experimental setup (3)
The Universal Testing Machine apparatus was used to
conduct quasi-static axial loading. The test was performed at a By substituting Eq. (3) into Eq. (4), the coefficient vector
rate of 6 mm/ min. Specimens will be axially deformed can be measured.
between two parallel steel flat platens consists of fixed and
moving platens. The fixed platen was connected with a load B. Analysis of variance (ANOVA)
cell where the load signal was taken directly to the computer. In this study, ANOVA was conducted to identify the effect
The specimens were crushed up to 70% of the length. The
impact test was performed using Dynatup drop weight impact of length of foam and thickness of the thin-walled structure in
tester. numerical intensity to energy absorption capability and initial
peak force. Each output response was analyzed individually
III. RESULTS AND DISCUSSION for the for both input factors. Table for ANOVA acquired by
using Design-Expert software
A. Optimization methodology consists of value of sum of
RSM has been dominant technique in crashworthiness square which is a variables that

optimization mainly because of it provides efficient and

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Optimization of Foam-Filled Square Thin-Walled Aluminium Structures

emerges as part of a general approach to present outcomes of estimation of value EA and IPF acquired from the response
such analysis, mean square which is a measurement of the
quality for an approximation, F-value is obtained with by functions and experimental results. The values of sum of
dividing two mean squares and decides the ratio of explained square, mean square, R2, R2-adj, p-value and F-value can be
variance to unexplained variance, P-value which is the level
of significance limits within a statistic hypothesis test to observed in Table III for quasi-static test and Table IV for
present the probability of the of a studied case[28]. For the
model to be significant, the P-value shall not more 0.05. The impact test. Suitability of the RS model can be measure by the
larger values of R2 and R2-adj (almost 1).

Table- III: ANOVA table for quasi static test

Output Source Sum of Mean F-value P-value R2 adj-R2 pred-R2
response squares 0.9946 0.986 significant
Model square
QS-EA Length 0.9927 0.9858 significant
Thickness 205500 68496 433.39 <0.0001 0.9969
QS-IPF Residual 51825.6 51825.6 327.91 <0.0001 0.9948
Std. Dev 134900 134900 853.47 <0.0001
Mean
Model 632.19 158.05 479.97 1.95
Length 12.57 C.V. % 28.22 2885.6
Thickness 643.8 PRESS < 0.0001
Residual 3382.75 931.72 0.0032
Std. Dev 6765.5 198.92 < 0.0001
Mean 198.92 6566.58
6566.58 4.08
7.05 96.54
35.24 C.V. %
2.65 PRESS

65.08

Table- IV: ANOVA table for impact test

Output Source Sum of Mean F- P- R2 adj-R2 pred-R2
response squares square value value

IMP- Model 165900 82963.05 2739.86 < 0.0001 0.9991 0.9987 0.9974 significant
EA Length 1188.1 1188.1 39.24 0.0015
Thickness 164700 164700
IMP- Residual 30.28 5440.49 < 0.0001
IPF Std. Dev 151.4 C.V. %
Mean 5.5 PRESS 57.15 1.42 0.9581 0.9413 0.8844 significant
Model 18.53 439.44
Length 388.75 2807.31 95.77 0.0004
Thickness 5614.62 910.12 0.0077
Residual 4704.5 2739.86 0.0002
Std. Dev 910.12 49.12 39.24
Mean 4704.5 < 0.0001 0.9991 0.9987 0.9974 significant
82963.05
245.6 1188.1 0.0015
165900
1188.1 R2 value suggest the desirability of the output model
projection. Value of R2 is 0.9969 is in reasonable agreement
 ANOVA of energy absorption responses for quasi-static with the R2-adj which is 0.9946. The higher value of R2 relates

and impact test. to the higher accuracy of the RS model. Therefore, for EA,

For quasi-static test, energy absorption obtained a linear two factor interaction (2FI) is found to be the best

model solution. The p-value is smaller than 0.05 indicates that approximation compared to other response functions. The
the model term is significant. Value of R2 shown the outcome
equation in terms of actual factor obtained for the energy
of any input factor studied in the model, that influence the
effect in the output responses. While value of R2-adj specify absorption response in

the actual outcome of the model input factor on the output quasi-static test is stated in Eq.
responses. The higher value of R2-adj and its accuracy to the
(4).

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(4) (7)
While in impact test, value of R2 is 0.9991 is in reasonable C. Validation of the RS models
agreement with the R2-adj which is 0.9987. Similar to Figure 3 shown a scatter diagrams for the distribution of the
Tran[33] study ,linear function is found to be the best actual values acquired from the experiment vs the predicted
approximation for EA. The equation in terms of actual factor values from output model for each output response. From the
obtained for the energy absorption response in impact test is diagram, the distribution of the point that located near the
stated in Eq. (5) diagonal line reflects the model ability to predict the response
trends
(5) D. Crashworthiness optimization for quasi-static test
 ANOVA of initial peak force responses for quasi-static The experimental data used in this study can be observed
and impact test. clearer in Figure 3 that shows the variation in EA and IPF
The results for the IPF response of both quasi-static and respectively with thickness and length. It shown that that both
impact test led to a linear model with a relationship between EA and IPF increase with the increment in thickness.
length of foam, L and thickness, t. Value of R2 for quasi-static Moreover, the EA and IPF displays the decrease trends with
test is 0.9948 is in reasonable agreement with the R2-adj decreasing of length of foam. As for in this study, the structure
which is 0.9927. It indicates the output model ability to is optimized with the length and thickness as the input factor
predict the response behavior. Model is defined as and EA and IPF as the output response formulated in
significance condition when value of p< 0.05. While for IPF Equation 1. EA and IPF are modeled by the linear
in quasi-static test, the linear function should be used for the polynomials. RS approximation approach as in [35] has been
optimum design. The equation in terms of actual factor was adopt to obtain the better responses. The optimum solutions
obtained as Eq. (6) for quasi-static test are shown in Table-V, there are 4 design
While in impact test, value of R2 is 0.9581 is in reasonable solution were suggested. But according to the desirability
agreement with the R2-adj which is 0.9413. Linear function is value, the first solution with 200mm length of foam and
found to be the best approximation compared to other 1.87mm thickness were selected to obtain 864.5 J of EA and
response functions. The equation in terms of actual factor 88.3 kN of IPF. The optimum results for EA and IPF for
obtained for the energy absorption response in impact test is quasi-static test can be observed in in Figure 4.
stated in Eq. (7)

(6)

Fig. 3. Predicted versus experimental graph (a) Energy absorption response (quasi-static), (b) Energy absorption
response (impact), (c) Initial Peak Force response (quasi-static), (d) Initial Peak Force

response (impact)

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Optimization of Foam-Filled Square Thin-Walled Aluminium Structures

Table- V: Design solution given by Design Expert impact test for the optimum value of EA and IPF. But for the
software for quasi-static test higher value of desirability, the selected design solution is
185mm of foam length with 2.0 mm thickness of the column
S to achieve the optimal value of EA and IPF which is 515.9J
and 134.94kN respectively. Variation of thickness and length
ol Length Thick EA IPF Desirability of foam with EA and IPF were shown in Figure 5
ut (mm) ness (J) (kN)
io (mm) Table- VI: Design solution given by Design Expert
software for impact test
n

1 200 1.87 864.47 88.33 0.641

2 200 1.88 865.85 88.54 0.641 Solutio Length Thickness EA IPF Desirability
n (mm) (mm) (J) (kN) 0.79
3 200 1.87 862.69 88.08 0.641 185 2 515.9 134.9
1 0.789
4
4 200 1.88 868.60 88.94 0.641 2 185.08 2 516.0 135.1

8

E. Crashworthiness optimization for impact test 3 185 2 514.6 134.7 0.788
3 0.785
The same optimization process as in above section was 4
conducted for impact test, the optimum design variables for 134.4
the test are summarized in Table VI. There are 4 4 185 1.99 512.8 2
configurations of length and thickness are suggested for
2

(a) Design-Expert® Software (b)

Design-Expert® Software Initial Peak Force
162
Energy absorption
542 Fig 4.(a) Effect of L and t to EA for quasi-st8a9.3tic test (b) Effect of L and t to IPF for quasi-static test

224 X1 = A: Length
X2 = B: Thickness
X1 = A: Length
X2 = B: Thickness

164
550

Energy absorption - impact 467.5 Initial Peak Force - impact 144.5

385 125

302.5 105.5

220 86

2.00 200.00 2.00 200.00
1.85
1.70 196.25 Design-Expert® Software 1.85 196.25
1.70
thickness, t Design-Expert® Software 192.50
thickness, t
192.50 Initial Peak Force

1.55 188.75 Energy absorption 162 1.55 188.75 length, L
542 185.00
length, L

1.40 185.00 224 89.3 1.40

X1 = A: Length X1 = A: Length
X2 = B: Thickness X2 = B: Thickness

(a) 550 164 (b)

Fig 5.(a) Effect of L and t to EA for impact test (b) E467f.5fect of L and t to IPF for impact test
Energy absorption - impact
much affected by th14e4.5thickness of tubes and length of foam
Initial Peak Force - impact
IV. CONCLUSION that fil3l8e5d in the tubes. Therefore, thickness and length of
foam 3w02e.5re selected a12s5the input factor for the optimization.
This paper discussed optimization design for foam-filled
square tubes subjected to quasi-static and impact test. The Response surface 1m05e.5thod (RSM) was used to produce
maximum of EA and minimum IPF are considered as the 220
objective function. By using historical data design from response functions of EA and
experimental, it was found that the value of EA and IPF were
IPF. 2.00 86 200.00

1.85 196.25

1.70 192.50

thickness, t 1 .5 52 .0 0 188.75 length, L 200.00
196.25
1.40 11.8855.00

Published By: 1.70 192.50

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International Journal of Recent Technology and Engineering (IJRTE)
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The optimization showed that the optimum EA and IPF for 18. M. Yang, B. Han, P. Su, Z. Wei, Q. Zhang, and Q. Zhang, “Axial

quasi-static was found to be 864.47J and 88.33kN crushing of ultralight all-metallic truncated conical sandwich shells
with corrugated cores,” Thin Walled Struct., vol. 140, no. December
respectively for foam length of 200mm and thickness of 2018, pp. 318–330, 2019.
19. R. Lu FangyunLi, Zhibin; Chen, “Comparative analysis of
1.87mm. While for impact test, the optimum value of EA is crashworthiness of empty and foam-filled thinwalled,” Thin Walled
Struct., vol. 124, no. December 2017, pp. 343–349, 2018.
515.9J with IPF of 134.94kN for foam length of 185mm and 20. M. Paulino and F. Teixeira-dias, “On the Use of Polyurethane Foam
Paddings to Improve Passive Safety in Crashworthiness Applications,”
thickness of 2.0mm. pp. 30–32, 2012.

ACKNOWLEDGMENT 21. T. Y. Reddy, R. J. Wall, M. Engineering, P. O. Box, and M. M. Iqd,
“AXIAL COMPRESSION OF FOAM-FILLED CIRCULAR TUBES,”
The author would like to acknowledge the support of the Int. J. Impact Eng., vol. 7, no. 2, pp. 151–166, 1988.

internal grant of Universiti Malaysia Pahang, RDU180316, 22. N. Onsalung, C. Thinvongpituk, and K. Pianthong, “Impact Response
of Circular Aluminum Tube Filled with Polyurethane Foam,” Mater.
RDU160140, PGRS190337 and support provided by the Trans., vol. 55, no. 1, pp. 207–215, 2014

Ministry of Higher Education, Malaysia under Fundamental 23. L. Yan, N. Chouw, and K. Jayaraman, “Lateral crushing of empty and

Research Grant Scheme, FRGS/1/2016/TK03/UMP/02/22 polyurethane-foam filled natural flax fabric reinforced epoxy
composite tubes,” Compos. Part B Eng., vol. 63, pp. 15–26, 2014.
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2016, pp. 106–118, 2017. AUTHORS PROFILE
11. J. Fang, Y. Gao, G. Sun, G. Zheng, and Q. Li, “Dynamic crashing
Nurul Izzah bt Ab Rahim, Possess Bachelor
behavior of new extrudable multi-cell tubes with a functionally graded
thickness,” Int. J. Mech. Sci., vol. 103, pp. 63–73, 2015. Degree in Mechanical Engineering from Universiti
12. X. An, Y. Gao, J. Fang, G. Sun, and Q. Li, “Crashworthiness design for
Teknologi Malaysia, Skudai, Johor Bahru, Johor in
foam- fi lled thin-walled structures with functionally lateral graded
thickness sheets,” Thin Walled Struct., vol. 91, pp. 63–71, 2015 2000. Currently working as lecturer in Politeknik
13. G. Zheng, T. Pang, G. Sun, S. Wu, and Q. Li, “Theoretical, numerical,
Muadzam Shah. Now doing research on energy
and experimental study on laterally variable thickness (LVT) multi-cell
tubes for crashworthiness,” Int. J. Mech. Sci., vol. 118, no. June, pp. absorption capability of foam-filled
283–297, 2016.
14. G. Li, Z. Zhang, G. Sun, F. Xu, and X. Huang, “Crushing analysis and thin-walled structure.

multiobjective optimization for functionally graded foam-filled tubes Salwani binti Mohd Salleh.Author obtained her
under multiple load cases,” Int. J. Mech. Sci., vol. 89, pp. 439–452,
Bachelor Degree in Manufacturing Engineering from
2014.
International Islamic University Malaysia in 2004, Master
15. E. Mahdi, A. S. Mokhtar, N. A. Asari, F. Elfaki, and E. J. Abdullah,
“Nonlinear finite element analysis of axially crushed cotton fibre in Engineering Management in 2006 and followed by PhD
composite corrugated tubes,” Compos. Struct., vol. 75, pp. 39–48,
in Mechanical Engineering in 2013 from Universiti Putra
2006.
16. A. Eyvazian, T. N. Tran, and A. Magid, “Experimental and theoretical Malaysia. Currently, author works as senior lecturer in

studies on axially crushed corrugated metal tubes,” Int. J. Non. Linear. Universiti Malaysia Pahang
Mech., vol. 101, no. February, pp. 86–94, 2018.
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sandwich tubes with lateral corrugated tubes in the middle for energy
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303–317, 2019.

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Discovering the Readiness of Malaysian
Industry in Adaptation of Industrial Revolution

4.0 towards Manufacturing Sustainability

M.N.H.M. Rosdi, M.R. Muhamad, W.H.W. Mahmood, M.H.A. Kadir

Abstract: Industrial revolution 4.0 is hitting manufacturing I. INTRODUCTION
industry where a big amount of data and equipment are being
introduced. There are many definition of IR 4.0 defined by This section concentrated on current situation and certain
researchers and industrialists from the whole world. Some of the
popular definition are customization, digitalization, flexible, concepts that are adapted and implemented in this research.
responsiveness and automation. This paper will focused only on The flow started with a brief discussion on Industry 4.0 (IR
one element of IR 4.0 which is responsiveness. Responsiveness 4.0) before narrowed down the scope into manufacturing
holds an essential role in IR 4.0 where manufacturing firms have responsiveness (MR) as one of essential element in Industry
to be responsive on the whole manufacturing process related with 4.0. In this research, MR practices act as independent variable
their business from the production design, planning, customer, in discovering its interaction or impact on manufacturing
society, surrounding, technology, suppliers and stakeholders. On sustainability (MS) which is dependent variable. Lastly,
the other hand, lots of issues related with sustainability are arise literature on MS is extracted where it has a further
either from governed authority or non-government bodies. This well-known classification environmental, economical and
issue is very sensitive and should be considered by manufacturing social sustainability.
firms in any decision made. This scenario makes IR 4.0 and A. Industrial Revolution 4.0
sustainability looked moving in the opposite direction where
achieving and competing in IR 4.0 will make manufacturing IR 4.0 has been an influence factor in manufacturing
firms neglecting the sustainability issue. In order to be more industry where most manufacturing firms have been chasing
sustainable in this industry, manufacturing firms should consider towards it. There are several terms to define IR 4.0 according
to be responsiveness and its impact towards manufacturing to published articles. IR 4.0 emphasizes the usage of internet
sustainability. This research started with finding the key connection, high end technology and digitalization to meet
manufacturing responsiveness and sustainability practices and customer requirements [1]. Wang [2] expressed that IR 4.0 is
elements from the published articles. Then, a structured leveraging various elements in manufacturing namely IT
questionnaire survey is constructed thus distributed to reachable based communication, tools, machines, IT interaction
manufacturing firms in Malaysia. The data gathered is analyzed services and products. Wang [2] also divided IR 4.0 into four
using SPSS software on the data reduction and factor analysis, components which is cyber physical system, mobile and cloud
Cronbach’s alpha reliability test and Pearson correlation. The computing internet of thing (IoT), big data and knowledge
result proved that Malaysian industry is very well aware and discovery, and internet of services (IoS). From other
prepared regarding manufacturing responsiveness and perspective, IR 4.0 consisted of four aspects: (1) factory, (2)
sustainability as well as manufacturing management. When business, (3) products and (4) customers where these aspects
analyzed deeper, research found that Malaysian industry is lack expressed as the main vision in any manufacturing firms [3].
or considered weak in competitiveness thus it is essential in future
to focus on this area.

Keywords: Industry revolution 4.0, manufacturing
responsiveness, manufacturing sustainability

Revised Manuscript Received on November 19, 2019 Fig. 1: Enabling Technologies of IR 4.0 [1]
* Correspondence Author
Figure 1 listed all the related essential technologies to be
Mohd Noor Hanif Mohd Rosdi*, Department of Quality and integrated in achieving IR 4.0.
Productivity, Kolej Kemahiran Tinggi MARA, KM8, Jalan Gambang 25150
Kuantan, Pahang, Malaysia. Email: [email protected] By all the IR 4.0 components, definitions and technologies,
the main objective is fulfilling customer demands. The market
Mohd Razali Muhamad, Department of Manufacturing Engineering, and customer requirements that keep changing with lots of
University Technical Malaysia, 76100 Malacca, Malaysia. Email: variety and customization need
[email protected] every manufacturing firm to be
responsive [4]–[6]. It can be
Wan Hasrulnizzam Wan Mahmood, Department of Engineering
Technology, University Technical Malaysia, 76100 Malacca. Email:
[email protected]

Mohd Hafiz Abd Kadir, Department of Technology and Process, Kolej
Kemahiran Tinggi MARA, KM8, Jalan Gambang 25150 Kuantan, Pahang,
Malaysia. Email: [email protected]

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& Sciences Publication

Discovering the Readiness of Malaysian Industry in Adaptation of Industrial Revolution 4.0 towards
Manufacturing Sustainability

clinched that one of the main outcome of IR 4.0 is to be a II. METHODOLOGY
responsive manufacturing firm. Manufacturing
responsiveness here not only limited to customer oriented [1], This research started with cross reference research articles
[6], it also included supply chain responsiveness [5], from 2008 until 2017 on IR 4.0, MR and MS as implemented
responsive manufacturing system [2], responsive to market by Mohd Rosdi et al. (2016) where matrix form developed to
trends changes [7] and responsive towards quick changeover systematically review all related literature on specific field.
[3]. There are various manufacturing responsiveness The review has come out with 18 elements of MR practices
perspective thus categorized it will give a valuable input into and 10 practices each for SE, SN and SC as an initial elements
this field. to be included in the questionnaire survey. The questionnaire
survey implemented five Likert scale as respondents
B. Manufacturing Responsiveness agreement with the practices listed. A total of 200 sets of
questionnaire survey have been distributed by mail, e-mail
In this research, MR appears to be a variable that represent and by-hand, only 51 were returned. Thus the responds is
IR 4.0. As stated earlier, MR covers a wide range of analyzed using software IBM Statistical Package for Social
manufacturing phase from supplier until customer. Table 1 Science (SPSS) with the chosen three analysis: (1) Data
summarized the MR areas that have been highlighted by reduction and factor analysis (2) Cronbach’s Alpha reliability
published research. analysis and (3) Pearson Correlation analysis. The result
obtained from these analyses will be used to construct a
Table-I: Highlighted Manufacturing Responsiveness framework represent the flow of IR 4.0 or MR adaptation
Area towards MS particularly in Malaysian industry.

NO AREA REFERENCE III. RESULT
1 Customer/Market [8]–[11]
2 Supply Chain [12]–[16]

3 Production Line/Operation [9], [17], [18]

4 Product [11], [13] A. Data Reduction and Factor Analysis
[18]–[22]
5 Organization/Human This analysis is proposed to eliminate and classify the
Management elements consisted in the questionnaire survey distributed.
The pattern of data gathered from all the respondents could
In general, [18] defined MR as overall property including determine both insignificant elements and then classify the
human resources and machines that react to external changes elements within a group into several sub classifications.
especially which that will give disturbance to their current Before decided to eliminate and classify the elements, the
manufacturing system. It is clear that MR scope not only value of Kaiser-Meyer-Olkin (KMO) measure must be greater
limited to machines and technology but also human resources. than 0.6 and Significant (Sig.) Less than 0.05 in KMO and
Bartlett’s Test. In eliminating any element, there are two main
C. Manufacturing Sustainability point which needed to be examined in detail which are
bi-factor element and low factor loading (less than 0.5) [28].
Manufacturing sustainability is a crucial circumstances Lastly, it is essential to recheck the Cronbach Alpha
where all manufacturing firms struggling to achieve. Besides Reliability value to be greater than 0.6.
the rapid improvement of technology, MS should not be
neglected to ensure the continuity of business [23]. MS has Concentrated back to this research, all the main
been discussed widely by lot of research made, thus it has its components namely manufacturing responsiveness (MR),
well-known three components namely environmental environmental sustainability (SE), economical sustainability
sustainability (SE), economical sustainability (SN) and social (SN) and social sustainability (SC) are undergone this data
sustainability (SC) [23]–[25]. The importance of MS in IR reduction and factor analysis. The result of MR is shown in
4.0 also has been improvised by Morrar [7] in a framework as Table II below.
shown in Figure 2. Figure 2 concluded the importance of MS
as it also visualized as one of the mission in IR 4.0. Roberts & Table-II: Data Reduction and Factor Analysis for
Ball (2014) has developed a library of manufacturing Manufacturing Responsiveness
sustainability practices to be adapted by other research. The
importance of MS in manufacturing industry as well as CLASSIFICATIONS
committing to IR 4.0 environment drive this research
INTERNAL COMPETITIVE INNOVATION
MR2
MR5 MR4 MR8
MR9
KMO MEASURE MR11 MR7 MR10
= 0.794
SIG. = 0.00 MR14 MR17 CRONBACH’S
ALPHA = 0.787
MR15

MR18 CRONBACH’S

CRONBACH’S

ALPHA = 0.807 ALPHA = 0.788

Fig. 2: Framework of Sustainable Industry 4.0 [7] Table II shows that the analysis has eliminated six out of 18
elements in manufacturing responsiveness; MR1, MR3, MR6,
to discover the interaction of MR as an element of IR 4.0 with MR12, MR13 and MR16. MR1 and MR16 were eliminated
respect to MS represented by SE, SN and SC. due to insufficient element in a classification resulted from
factor analysis. The ideal number of element in a
classification should be at least three. The other four elements
were rejected reflected from low
factor loading (smaller than
0.5). These circumstances left

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International Journal of Recent Technology and Engineering (IJRTE)
ISSN: 2277-3878, Volume-8 Issue-4, November 2019

only 12 elements where factor analysis classified them into B. Highlighted Correlation between Manufacturing
three namely internal responsiveness, competitiveness and
innovation. The elements lied on those three classifications Responsiveness and Sustainability
are as listed in Table II.
All responds are analyzed by Pearson’s correlation
Next components to be undergo the analysis is
manufacturing sustainability. As widely known and studied analysis. Correlation analysis is important in order to
done on MS, it cannot be separated with its three components;
SE, SN and SC. The analysis also will be done by these three determine which independent and dependent variable have
segregations starting with SE, SN and lastly SC where each
come with 10 elements initially. Table III shows the result on significant similar reaction or relate tightly among them.
SE.
Usually most of them will have a positive correlation where
Data reduction analysis only eliminated one element of SE
which is SE4. As stated in Table III, there are two this research will be highlighted on the top of the cream. Table
classifications of SE where suited to be entitled as controlling
and avoiding environmental pollution. SE5, SE6, SE7, SE8, VI will simplified the result for Pearson correlation.
SE9 and SE10 listed under controlling while SE1, SE2 and
SE3 listed under avoiding. Table IV represent the result for The result from Pearson correlation on this research
the second MS component (SN) while Table V represent the
last SC as the last MS component. elements giving most of them correlate positively each other.

Table-III: Data Reduction and Factor Analysis for There is only one relation is negative but it is not significant
Environmental Sustainability
(-0.032 between MR7 and SN9). The result of Pearson

correlation is divided into positive or negative correlation,
significant correlation (0.01 < Sig. ≤ 0.05) and strongly
significant correlation (Sig. ≤ 0.01). Table 5 listed all MS

elements with strong significant correlation corresponding to

MR elements. The distribution of MS elements from Table 5

clearly resulted on competitive responsiveness not really has

significant correlation with MS supported by none from SE

and SC has strong significant correlation with MR7 (consider

CLASSIFICATIONS investment trade off).
Table-VI: Summary of Pearson’s Correlation Analysis
CONTROLLING AVOIDING

SE5 SE1 Manufacturing ELEMENTS WITH SIGNIFICANT AT THE
SE6 SE2 Responsiveness 0.01 LEVEL
SE7 SE3
KMO MEASURE = SE8 Environm Economical Social
0.804 SE9 CRONBACH’S ental Sustainability Sustainability
SE10 ALPHA = 0.710
SIG. = 0.00 Sustainabi
CRONBACH’S lity
ALPHA = 0.927
MR5 SE5, SE6, SN6, SN8 SC2, SC9
SE7

Table-IV: Data Reduction and Factor Analysis for MR11 SE3 SN1, SN5, SC2, SC5, SC9,
SN6, SN7, SC10
Economical Sustainability
SN8
CLASSIFICATION
MR14 SE1, SE3, SN2, SN3, SC1, SC2, SC3,
ECONOMICAL SE6, SE7, SN5, SN6, SC4, SC5, SC7,
SN7, SN8 SC8, SC9, SC10
SN1 Internal SE9,
KMO MEASURE SN5 SE10
= 0.68 SN6
SN7 MR15 SE5, SE6, SN2, SN3, SC2, SC3, SC4,
SIG. = 0.00 SN8 SE7, SE9, SN5, SN6, SC5, SC6, SC7,
SN7, SN8 SC8, SC9, SC10
CRONBACH’S ALPHA = SE10
0.802
MR18 SE5, SE7, SN1, SN5, SC2, SC3, SC4,
SE8, SE9, SN6, SN7, SC5, SC6, SC7,
Table-V: Data Reduction and Factor Analysis for Social SC8, SC9, SC10
Sustainability SE10 SN8

CLASSIFICATION Competitive MR4 SE6, SE7, SN6, SN7, SC6
SOCIAL MR7 SE8 SN8
SN7
KMO MEASURE ALL SC1 – SC10
= 0.886 MR17 SE2, SE7, SN7, SN8 SC6, SC7, SC8,
CRONBACH’S ALPHA =
SIG. = 0.00 0.939 SE8 SC10

MR2 SE2, SE7, SC8

SE8,

Both Table 3 and Table 4 have similar table pattern where SE10
factor analysis classified them only into a single
classification. The classification named as the original MR8 SE1, SE2, SN7, SN8, SC5, SC9, SC10
components which are economical and social sustainability.
Detail view on Table 3 discovered that only five elements left Innovation SE5, SE6 SN9, SN10
out of ten. SN elements that are accepted here are SN1, SN5,
SN6, SN7 and SN8. Only SN4 eliminated by poor factor MR9 SE5, SE6, SN2, SN6, SC1, SC2, SC3,
loading while the other four had to be left because insufficient
number of element in a classification. Lastly, data reduction SE7, SE8, SN8, SN9 SC5, SC8, SC9,
and factor analysis on SC resulted as the most reliable with
highest KMO measure among four components that SE10 SC10
undergone the analysis. SC also seems to be the best
component by the acceptance of all its 10 elements in factor MR10 SE2, SE3, SN1, SN2, SC2, SC5, SC8,
analysis and holds the highest reliability Cronbach’s Alpha
value with 0.939. SE5, SE6, SN6, SN7, SC9, SC10

SE7, SE8, SN8

SE10

* Elements in red represent the highest correlation value with the

corresponding manufacturing responsiveness element

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Discovering the Readiness of Malaysian Industry in Adaptation of Industrial Revolution 4.0 towards

Manufacturing Sustainability

It is quite hard when comparing between community and ensure that the assumptions and suggestions are reliable to be
information responsiveness but when listed according to MR
elements, MR2 (redesign production line for new product) adapted in real industry practice or to be implemented by
none correlate significantly with SN. The result may
interpreted differently from the other perspective, where SN6 researchers.
(minimize transportation cost) lead others with three times
held the highest correlation value; MR5 (use new resources), ACKNOWLEDGEMENT
MR11 (treated all department similarly) and MR14 (adequate
support). This ranking followed by SE2 and SN8 where both This research is co-funded by Majlis Amanah Rakyat
elements appeared top twice.
(MARA), University Technical Malaysia Malacca (UTeM)
In next section, the summary of both results are discussed
which this research will suggested an info-graphic summary under grant (FRGS/2016/FTK-AMC-/F00324) and MyPhD
to make it more understandable.
under Ministry of Education.
IV. DISCUSSION
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AUTHORS PROFILE

Mohd Noor Hanif Mohd Rosdi graduated bachelor in
Manufacturing Engineering from International Islamic
University Malaysia. Master Degree in Manufacturing
System Engineering from University Putra Malaysia.
Currently pursuing PhD at University Technical
Malaysia Malacca. Served as Vocational Training
Officer with Majlis Amanah Rakyat (MARA).

Prof Datuk Dr Mohd Razali Muhamad has long
served at University Technical Malaysia Malacca and
currently held the Deputy Vice Chancellor (Academic &
International) there. Education background in
Manufacturing Engineering. He is a very well-known
figure in manufacturing field with lot of experience.
Graduated bachelor and Master in Production
Engineering and Management from Loughborough University, UK before
PhD in Manufacturing System from The University of Liverpool UK.

Assoc. Prof Dr Wan Hasrulnizzam Wan Mahmood
currently held the position of Deputy Dean (Academic)
in Faculty of Engineering Technology University
Technical Malaysia Malacca. Graduated Bachelor
degree in Manufacturing Management from University
Technology Malaysia and later master in Quality and
Productivity Improvement from University Kebangsaan
Malaysia. He Graduated his PhD also from University Kebangsaan Malaysia
in Mechanical and Material Engineering.

Mohd Hafiz Abd Kadir graduated from University Tun
Hussien Onn Malaysia in Mechanical Engineering
before further study at University Putra Malaysia in
Master of Manufacturing System Engineering. Served as
Vocational Training Officer with Majlis Amanah
Rakyat (MARA).

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ISSN: 2277-3878, Volume-8 Issue-4, November 2019

Effect of Drying Duration on Production of
Sabah Snake Grass (Clinachantus Nutans)

Botanical Drink

Zaleha Ismail, Siti Nasiroh Ismail, Norehan Aziz

Abstract: This study was carried out to investigate the effect of When botanical beverages mix is produced in
drying duration of Sabah Snake Grass (Clinachantus Nutans) ready-to-drink form it shall be construed as botanical
botanical drinks on sensory properties, total phenolic content beverages (Food Act 1983 and Regulations). Drying process
(TPC) and free radical scavenging activity (FRSA). Three types of is considered to be the best way to protect the phytochemical
drinks samples were produced using a Sabah Snake Grass leaves efficiency in herbal plants [3]. It also has the advantage of
which dried by oven method at temperature 45oC for 2 days for reducing the cost of the final product and the most frequently
Formulation 1 (F1), 5 days for Formulation 2 (F2) and without used operations to expand the shelf life of food [4]. This study
drying (FS). Sensory analysis is performed to determine the level focused on the effects of drying time of C. nutans leaves on
of panel acceptance of attribute such as color, taste, aroma and sensory properties, total phenolic content and antioxidant
overall acceptance of Sabah Snake Grass drinks. Next, all properties of drinks.
samples were analyzed to determine total phenolic content and
antioxidant effect via 2, 2-diphenyl-2-picrylhydrazil (DPPH) II. METHODOLOGY
scavenging activity. For sensory analysis, F2 resulted highest
acceptance level by panelist compared to F1 and FS for all A. Materials
attributes and overall acceptance. Based on the result, F2 also
showed highest total phenolic content (0.78 ppm) and highest Fresh leaves of Sabah Snake Grass were collected from
percentage of inhibition compared to other samples. The results Sultan Haji Ahmad Shah Agricultural Park, Kuantan, Pahang.
showed drying process could increase the acceptance level of The leaves were washed with water and cut into small size
panelist, phenolic content and scavenging activity of the Sabah with a clean scissor. The other materials used in making
Snake Grass drinks. Sabah snake Grass drink were sugar, filtered water and citric
acid. Folin-Ciocalteau, Na2CO3, deionised water, methanol,
Keywords : Antioxidant activity, Phenolic content, Sabah and DPPH. The tools used were gas stove (Niko), stainless
Snake Grass, Sensory analysis steel pan, infrared thermometer (Krisbow), blender (Philips),
refrigerator (Panasonic), UV-Vis spectrophotometer (UV-
I. INTRODUCTION 1800 Shimadzu), drying oven (Binder) and measuring
pipettes (Pyrex).
Sabah snake grass/ Belalai Gajah (Clinacanthus nutans) is
a herbal species that grow in tropical climate. The plant B. Drying process
originates in the tropics of Southeast Asia, especially
Thailand and Malaysia, and also grows in southern China [1]. The leaves samples were labeled and subjected
The plant is grows to a height of 1-3 m and the leaves are immediately to drying. The leaves were dried using the
shaped like a blade, long and narrow and the size is about following methods: (1) oven drying 45oC for 2 days (2) oven
0.5-4 cm wide and 2.5-13 cm long [2]. Sabah snake grass is drying 45oC for 5 days. Fresh sample is used as a control (C).
used to treat some of health problems such as cancer, high
blood pressure, high uric acid, diabetes and reduce the risk of
clogged blood vessels. Due to less consumption by
community in Malaysia, various varieties of commercialized
products from Sabah Snake Grass such as teas and drinks
have been introduced in order to get benefit from this plant.
According to Malaysia Food Act 1983 and Regulations
(Regulation 356), it state that botanical beverages mix should
be a preparation made from edible or extractable plants or
herbs, with or without sweeteners and other foods.

Revised Manuscript Received on November 19, 2019 (a) (b)
Zaleha Ismail, lecturer in the department of Food Technology at Fig. 1. Fresh Sabah Snake Grass (a) and after drying (b)

Polytechnic Sultan Haji Ahmad Shah, Kuantan, Pahang, Malaysia. C. Production of drink samples
Siti Nasiroh Ismail, lecturer in the department of Food Technology at

Polytechnic Sultan Haji Ahmad Shah, Kuantan, Pahang, Malaysia.
Norehan Aziz, lecturer in the department of Food Technology at

Polytechnic Sultan Haji Ahmad Shah, Kuantan, Pahang, Malaysia.

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Effect of Drying Duration on Production of Sabah Snake Grass (Clinachantus Nutans) Botanical Drink.

The dried leaves were then added with water at ratio (1:60) (dislike) for FS respectively (Table 2). It was believed that
their aroma were coming only from the samples themselves
and boiled for 15 minutes. The fresh sample without drying because no other flavors were added to the sample
production. Results show that variation score for aroma
process is directly boiled in water to obtain its extract. After acceptability of drink obtained from different drying
duration. Increase drying duration of leaves resulted more
cooling process the leaves extract were filtered using filter acceptability of panelist. This result has been previously
shown by previous research that longer drying duration of
cloth to obtain clear liquid. Then, the extract was mixed with tea leaves caused the increasing the aroma [7].
 Color
sugar and heated to 90ºC. Citric acid was added to the mixture Mean scores showed significant difference between FS
samples for color (Table 2) compared to F1 and F2
and left for 5 minutes. The drinks was cooled and stored for samples. It was observed that the control sample (FS)
scored the lowest (2.83) than F1 (4.37) and F2 (5.12) for
further analysis. The formulation of drink is shown as below: color. The result indicate that increase the drying duration
caused the acceptability of color by panelist. According to
Table- I: Formulation of Sabah Snake Grass Drink During drying process, the loss of moisture could affect
organoleptic parameters, such as color and taste [3]. The
Ingredients Percentage (%) higher color acceptance by panelist (P<0.05) for F1 and F2
was due to drying process of the leaves. During drying the
Leaves extracts 45 chlorophylls were degraded to pheophytin which resulted
the less dark green color of drink sample [8].
Filtered water 44.9  Taste
Panelist responses on taste acceptability showed that drink
Sugar 10 sample F2 (drying duration 5 days) was better than sample
FS and F1. F2 was showed no significant result compared
Citric acid 0.1 to F1 but it showed significant result while compared to FS.
The result showed that longer the drying duration increase
D. Sensory analysis the acceptability of drink. This might due to production of
flavor during drying process.
A fifty member untrained panelists were used to evaluate  Overall acceptance
Results show that drink sample using leaves that drying for 5
the various sensory parameters (aroma, color, taste and days had the highest mean score in overall acceptability
(5.42) as shown in Table 2. This was expected as it was the
overall acceptability) and the scores were based on a 7 points most preferred product in color (5.12), aroma (5.00), and in
taste (4.69). This indicate that the product which were most
hedonic scale. The samples were assessed using 7 point accepted by the panelist with respect to their color, aroma,
and taste. However, fresh samples without drying process
hedonic scale ranging between 7 (like very much) to 1 (dislike showed lowest score for all attributes.

very much). Data obtained from analysis were evaluated Fig. 2. Sabah Snake Grass Drink

statistically using a variance analysis (One Way ANOVA).

E. Total Phenolic Content (TPC) Determination

Total phenolic content of juices was determined
spectrophotometrically according to Folin-Ciocalteu method
with slight modification [5]. An amount of 0.4 mL sample or
standard solution was added into 10 mL volumetric flask,

containing 3.6 mL of distilled water. Folin-Ciocalteu reagent

(0.4 mL) was added into the mixture. About 4 mL of 7%
sodium carbonate was also added following 5 min. The
solution was made up to 10 mL with distilled water, mixed
thoroughly and allowed to stand at room temperature for 90
min. The absorbance was measured at 765 nm using
UV-visual spectrophotometer (UV- 1800 Shimadzu) against
distilled water as blank. Calibration curve was plotted using
gallic acid standard solution of 0 – 100ppm.
F. Total Antioxidant Activity Determination

A modified method was used for estimating free radical

scavenging activity [6]. 4.0 ml of DPPH was mixed with 0.4
ml drink sample (diluted 10:40 with ethanol). The mixture
was allowed to stand for 30 min at room temperature (25OC)
after which its absorbance was measured at 517 nm using a
spectrophotometer (UV- 1800 Shimadzu), against ethanol as
blank. The free radical scavenging activity (FRSA) of the
tested sample was evaluated by comparing its absorbance
with the control. The free radical-scavenging activity was
measured by using this formula:

Inhibition (%) = [(AC - AS) / AC]×100% (1)

where AC = absorbance of control and AS = absorbance of

tested sample.

III. RESULTS AND DISCUSSIONS

A. Sensory properties

Sensory characteristic of Sabah Snake Grass drinks on
different formulation which include aroma, color, taste, and
overall acceptability are presented in Table 2.
 Aroma
The mean scores for aroma of drink samples were 5.00 (like)

for F2 and 4.17 (neither like nor dislike) for F1 and 3.13

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International Journal of Recent Technology and Engineering (IJRTE)
ISSN: 2277-3878, Volume-8 Issue-4, November 2019

Table- II: Results of sensory analysis for Sabah Snake
Grass drinks

Attributes Formulation (Sample) 80
Colour
FS F1 F2 60Antioxidant activity
2.83a ± 0.23 4.37b ± 0.57 5.12b ± 1.18 (% inhibition)
40
Aroma 3.13a ± 0.17 4.17b ± 0.51 5.00b ± 1.96
20
Taste 2.80a ± 0.21 4.37b ± 0.40 4.69b ± 1.22
0
Overall 2.83a ± 0.26 4.43b ± 1.10 5.42c ± 1.11 FS F1Fig. 4. Total Antioxidant Activity in different

Acceptance formulation of Sabah Snake Grass drinks

*Means within row with different letters indicate significantly different values (P<0.05). IV. CONCLUSIONS Sample

B. Total phenolic content in drinks samples The study investigated the effect of drying on sensory F2
attributes, phenolic content and antioxidant activity of Sabah
The effect of different time of drying (2 days, 5 days and Snake Grass drinks. Results showed that the sensory
fresh leaves) of Sabah Snake Grass were investigated in this properties of drink samples differ with respect to the drying
study. From Fig. 3, it can be seen that the trend of TPC for all duration used. Drink samples dried by oven at 45°C for 5 days
samples, where F2 recorded the highest value (0.78ppm) than (F2) was the most favored in color, aroma, taste and overall
F1 (0.662ppm) and FS gave the lowest (0.612ppm) value of acceptability. Oven drying at 45°C for 5 days was found to be
total phenolic content in Sabah Snake Grass drinks samples. most reasonable time for drying of Sabah Snake Grass leaves
This result might be due to the effect of drying process on in order increase appreciable sensory attributes. For total
leaves samples. Drying process could increases the rate of phenolic content, the longer drying duration of Sabah Snake
release of phenolic compounds from the food matrix as it can Grass leaves led to more phenolic content in drink sample. F2
break down cellular constituents in leaf samples [9]. Similar also showed the highest percentage of inhibition compared to
to the present study, oven drying method showed the highest other samples for antioxidant activity. The results from this
amount of phenolic compounds compared to fresh leaves study will be used as a guide to produce Sabah Snake Grass
because destructive enzymes were inactivated in dried leaves drink in improving the phenolic content and antioxidant
thus high levels of phenolic compounds remained in the activity of the drink products.
extract [4], [10].
ACKNOWLEDGMENT
C. Total Antioxidant Activity
The authors are grateful to the Department of Food
The effects of drying duration on Sabah Snake Grass drink Technology, Polytechnic Sultan Haji Ahmad Shah, Kuantan,
sample on antioxidant activity are shown in Fig. 4. Drying of Pahang, Malaysia for the support and facilities in conducting
Sabah Snake Grass leaves in oven for 5 days showed the this research. providing raw materials, instruments and
highest total antioxidant activity (62.56%) compared to F2 chemicals for this research. We also express thanks to the staff
(41.41%) and fresh drinks samples, FS (33.63%). The result of Sultan Haji Ahmad Shah Agricultural Park for their
showed total antioxidant activity (inhibition percentage) assistances in obtaining the samples.
increase when the duration of drying was increased. Similar
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DOI:10.35940/ijrte.D5424.118419 Blue Eyes Intelligence Engineering
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AUTHORS PROFILE

Zaleha Ismail is a lecturer in the department of Food
Technology at Polytechnic Sultan Haji Ahmad Shah,
Kuantan, Pahang, Malaysia. She presently has research
interest in Food Product Processing, Characteristic of
Food, Food Chemistry and Fats & Oils.

Siti Nasiroh Ismail is a lecturer in the department of
Food Technology at Polytechnic Sultan Haji Ahmad
Shah, Kuantan, Pahang, Malaysia. Her research area are
Food Product Processing, Characteristic of Food, Food
Microbiology and Food Biotechnology.

Norehan Aziz is a lecturer in the department of Food
Technology at Polytechnic Sultan Haji Ahmad Shah,
Kuantan, Pahang, Malaysia. Her research area are Food
Product Processing, Food Product Innovation and Food
Chemistry.

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International Journal of Recent Technology and Engineering (IJRTE)
ISSN: 2277-3878, Volume-8 Issue-4, November 2019

Development of Sustainable Supplier Selection
Model using Dematel for Manufacturing
Industry

Norhafiza Mohamed, Wan Hasrulnizzam Wan Mahmood, Muhamad Zaki Yusup,

Rahayu Tukimin

 manufacturing performance or competence, and economic or
financial performance. To develop the successful GSCM,
Abstract: A Sustainable Supplier Selection in supply chain there are requirement in selecting sustainable supplier.
becomes a key strategic evaluation to sustain in a competitive
manufacturing environment. Thus, a careful consideration in During late years, the thought of deciding supportable
supplier selection should be identified and prioritised. For this providers in the inventory network has become a key vital
reason, the studies were carried out to determine and analyse the thought. These is on the grounds that a viable and productive
elements that contributes to the establishment of the sustainable provider choice technique assumes a crucial job to the
supplier selection. To investigate the effectiveness of Sustainable accomplishment of an association [4]. Using environmental
Supplier Selection in the manufacturing Industry, a questionnaire criteria in supplier selection will improve the process of
was chosen to collect data from experts. Using a Decision Making getting a better GSCM. In this paper, analysis of
Trial and Evaluation Laboratory (DEMATEL) method a Causal implementation of Sustainable Supplier Selection in
model was then established. These model shows that the priorities manufacturing industry was divided into two that are Work
for Work System Performance (WSP) is WSP 4 (Manufacturing System Performance (WSP) and Work Responsive Practice
Cost Reduction). This finding is significant for manufacturing (WRP) WSP is the performance measured in the process of
firm to establish a sustainable supplier in the supply chain strategic decision making in the organization [5]. This
management. Highly focuses on all these factors as a part of in examination centers around Work System Performance
their decision making stage for supplier selection will ensure their (WSP) comprising of a Lead time decrease, WSP 1,
operation are in the sustainable manufacturing environment. Through-put time decrease WSP2, Work in progress
decrease WSP 3, Manufacturing cost decrease WSP 4,
Keywords : Sustainable Supplier Selection, DEMATEL, Work Product quality improvement WSP 5, Machine use
System Performance, manufacturing environment. improvement WSP 6, and adaptability improvement in
process WSP 7.
I. INTRODUCTION
The main goal of this paper is developing a framework
The development of manufacturing process has changed which can help to select Sustainable Supplier for GSCM. To
development of model, most review papers was using multi
follow with the innovation of high technologies. Changes in criteria decision making (MCDM) such as Analytic
this upheaval considered Supply Chain Management (SCM). Hierarchy Process (AHP), Analytic Network Process (ANP),
SCM is the incorporation key business forms from end-client Linear Programming (LP) and Data Envelopment Analysis
through unique providers that give items, administrations, (DEA) [6]. The model introduced by these papers is using
and data that additional incentive for clients and different DEMATEL. The selection of this tool because of the
partners [1]. For this purposes, supplier selection will give an specialist in suggestion in chooses the influential factors
impact to the environment by the process Green Supply between the elements.
Chain Management (GSCM). [2] believes that the
implementation of GSCM based on performance measures II. METHODOLOGY
such as environmental performance or green [3],
The DEMATEL method has been identified as the best
Revised Manuscript Received on November 19, 2019 tool available to identify the cause and effect relationship
* Correspondence Author among the criteria of evaluation. In order to identify the
interrelationship between the factors, or to examine and
N. Mohamed1,Kolej Kemahiran Tinggi MARA Balik Pulau, Genting create the cause and effect relationship among the criteria of
11000 Balik Pulau, Pulau Pinang, Malaysia. Email. evaluation [7]. Figure 1 shows the process of DEMATEL
[email protected] methods.

W.H.W. Mahmood2, Sustainable and Responsive Manufacturing
Research Group, Faculty of Engineering Technology, Universiti Teknikal
Malaysia Melaka, 76100 Melaka, Malaysia. Email:
[email protected]

M.Z.Yusup3, Kolej Kemahiran Tinggi MARA Balik Pulau, Genting
11000 Balik Pulau, Pulau Pinang, Malaysia. Email.
[email protected]

R.Tukimin4, Kolej Kemahiran Tinggi MARA Kuantan, KM8, Jalan
Gambang, 25150 Kuantan, Pahang, Malaysia. Email.
[email protected]

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Development of Sustainable Supplier Selection Model using DEMATEL for Manufacturing Industry

START Where ,

Gather experts’ opinion and calculate the λ
average matrix Z
1
Calculate the normalised initial direct- = max 1 < < =1[ ]
relation matrix D
1
Derive the total relation matrix T + max 1 < < =1[ ]

(4)

Equation 5 is used for the calculation and identification of the

total impact matrix (T).

= lim + 2 +. . . . +

→∞

(5)

Calculate the sums of rows and columns of = (1 − )−1
matrix T
(6)
Set the threshold value (a)
Vector r and c are used in order to depict the sum of rows and

columns in the total impact matrix (T)



= = ( =1 ) 1

Build a cause and effect relationship (7)
diagram
) 1
= 1 = (
=1

NO (8)

Is a cause and effect relationship The calculation of elemental average was done in matrix T to
diagram acceptable?
derive the threshold value of ∝.
=1[ ]
∝= =1

YES
The final cause and effect relationship
(9)

END III. RESULT AND DISCUSSION

Fig. 1 DEMATEL Process The normalized initial direct relation matrix D was
In gather experts’ opinion, a comparison scale is selected calculated that present in Table 3 from the value of
normalized initial direct relation matrix z based on tens
in comparing the relative importance degrees of components. expert perspective represent in Table 2. The total relation
The comparison scale consists of the following levels in matrix T was calculated using Eq. 5 and Eq. 6 as shown in
Table 4 (I), Table 5 (I-D), Table 6 (Inverse of I-D) and Table
Table I. 7 (T).

Table I : Scale of relative influence used in the pairwise TABLE II. The Normalised Initial Direct – Relation
Matrix, z

comparison matrix

Scale Linguistic variable WSP 1 WSP 2 WSP 3 WSP 4 WSP 5 WSP 6 WSP 7
WSP 1 0 2.6 2.9 3 2.2 2.3 2.9
0 No influence WSP 2 2.7 0 2.9 3.2 2.5 2.3 2.8
WSP 3 2.9 3.1 0 2.9 2.3 2.1 2.6
1 Low influence WSP 4 3.1 3.4 3.1 0 2.4 2.7 2.8
WSP 5 2.4 2.8 2.7 2.8 0 1.7 2.5
2 Medium influence WSP 6 2.4 2.4 2.3 2.7 2.1 0 2.8
WSP 7 2.8 2.7 2.7 3 2.7 2.6 0
3 High influence

4 Very High influence

The average matrix Z = [Zij] are the matrices from m experts

to aggregate all judgements from m experts is shown below.

1
=
=1

(1)

The worth of each element in matrix D is placed between

[0,1] and the normalized initial direct-relation matrix D is

denoted as .

= λ x Z

(2)

[ ] = λ [ ]

(3)

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ISSN: 2277-3878, Volume-8 Issue-4, November 2019

TABLE III. The Normalised Initial Direct- Relation cause factors. The importance of the evaluation perspective
Matrix D was determined by the ri+cj values. Based on Table 8, WSP 4
was the most significant evaluation perspective with the
WSP 1 WSP 2 WSP 3 WSP 4 WSP 5 WSP 6 WSP 7 largest ri +cj value = 22.0933, whereas WSP 6 is the least
significant perspective with the smallest ri+cj value =
WSP 1 0 0.147727 0.164773 0.170455 0.125 0.130682 0.164773 18.4013. With regards to the r + c values, the prioritised of
the importance of the seven evaluation perspectives seem s to
WSP 2 0.153409 0 0.164773 0.181818 0.142045 0.130682 0.159091 be WSP 4 > WSP 2 > WSP 7 > WSP 3,> WSP 1 > WSP 5 >
WSP 6.
WSP 3 0.164773 0.176136 0 0.164773 0.130682 0.119318 0.147727
TABLE IX. The average elements in matrix T
WSP 4 0.176136 0.193182 0.176136 0 0.136364 0.153409 0.159091

WSP 5 0.136364 0.159091 0.153409 0.159091 0 0.096591 0.142045

WSP 6 0.136364 0.136364 0.130682 0.153409 0.119318 0 0.159091

WSP 7 0.159091 0.153409 0.153409 0.170455 0.153409 0.147727 0

WSP 1 WSP 2 WSP 3 WSP 4 WSP 5 WSP 6 WSP 7 ri

TABLE IV. Total Relation Matrix T (I) WSP 1 1.3669 1.5456 1.5291 1.6013 1.3190 1.2897 1.5091 10.1607
WSP 2 1.5368 1.4554 1.5668 1.6491 1.3647 1.3212 1.5417 10.4358
WSP 1 WSP 2 WSP 3 WSP 4 WSP 5 WSP 6 WSP 7
WSP 1 1000000 WSP 3 1.5086 1.5670 1.3883 1.5978 1.3236 1.2810 1.4967 10.1629
WSP 2 0100000 WSP 4 1.6317 1.6982 1.6544 1.5787 1.4293 1.4056 1.6203 11.0182
WSP 3 0010000 WSP 5 1.4123 1.4772 1.4453 1.5136 1.1420 1.1985 1.4170 9.6059
WSP 4 0001000 WSP 6 1.3940 1.4404 1.4090 1.4899 1.2328 1.0948 1.4124 9.4732
WSP 5 0000100
WSP 6 0000010 WSP 7 1.5445 1.5918 1.5619 1.6447 1.3766 1.3373 1.4084 10.4652
WSP 7 0000001 71.3220 10.3948 10.7756 10.5548 11.0751 9.1880 8.9281 10.4056 cj
20.5556 21.2115 20.7177 22.0933 18.7939 18.4013 20.8708 ri +cj
∝ -0.2341 -0.3398 -0.3919 -0.0569 0.4179 0.5452 0.0596 ri - cj
1.4556 effect effect effect effect cause cause cause
P1 P6 P7
P5 P2 P4 P3

TABLE V. Total Relation Matrix T (I-D) In terms of the threshold value ( ∝) that represents the
interactions between perspectives, e.g. the values of WSP 2(1.5456 )
WSP 1 WSP 2 WSP 3 WSP 4 WSP 5 WSP 6 WSP 7 > ∝ (1.4556) hence the arrow in the cause and effect diagrams is
WSP 1 1.00000 -0.14773 -0.16477 -0.17045 -0.12500 -0.13068 -0.16477 drawn from WSP 2 to WSP 1 . The cause and effect diagrams of all
WSP 2 -0.15341 1.00000 -0.16477 -0.18182 -0.14205 -0.13068 -0.15909 sevens perspective is presented visually in Figure 2.
WSP 3 -0.16477 -0.17614 1.00000 -0.16477 -0.13068 -0.11932 -0.14773
WSP 4 -0.17614 -0.19318 -0.17614 1.00000 -0.13636 -0.15341 -0.15909
WSP 5 -0.13636 -0.15909 -0.15341 -0.15909 1.00000 -0.09659 -0.14205
WSP 6 -0.13636 -0.13636 -0.13068 -0.15341 -0.11932 1.00000 -0.15909
WSP 7 -0.15909 -0.15341 -0.15341 -0.17045 -0.15341 -0.14773 1.00000

TABLE VII. Total Relation Matrix T (inverse of I-D)

WSP 1 WSP 2 WSP 3 WSP 4 WSP 5 WSP 6 WSP 7

WSP 1 2.3669 1.5456 1.5291 1.6013 1.3190 1.2897 1.5091

WSP 2 1.5368 2.4554 1.5668 1.6491 1.3647 1.3212 1.5417

WSP 3 1.5086 1.5670 2.3883 1.5978 1.3236 1.2810 1.4967

WSP 4 1.6317 1.6982 1.6544 2.5787 1.4293 1.4056 1.6203

WSP 5 1.4123 1.4772 1.4453 1.5136 2.1420 1.1985 1.4170 FIGURE 2. A causal relationship for WSP
WSP 6 1.3940 1.4404 1.4090 1.4899 1.2328 2.0948 1.4124
WSP 7 1.5445 1.5918 1.5619 1.6447 1.3766 1.3373 2.4084 IV. CONCLUSION

TABLE VIII. The Relation Matrix T WSP activities are the performance that influences the
Sustainable Supplier. This paper used DEMATEL method of
WSP 1 WSP 2 WSP 3 WSP 4 WSP 5 WSP 6 WSP 7 analyse the WSP activities. The results were depending on
WSP 1 1.36692 1.545562 1.529114 1.601327 1.318992 1.289734 1.509079 data from threshold value, vector r and c. It is possible to
WSP 2 1.53685 1.455386 1.566812 1.649143 1.364687 1.321227 1.541729 conclude that there are two factors in WSP which is causes
WSP 3 1.508606 1.567038 1.388257 1.597765 1.323592 1.280956 1.496682 and effect. For the cause activities that are Product quality
WSP 4 1.63167 1.698228 1.6544 1.578686 1.429304 1.405576 1.620315 improvement WSP 5, Machine utilization improvement WSP
WSP 5 1.412308 1.477196 1.445316 1.513614 1.142026 1.198486 1.416972 6, and flexibility improvement in process WSP 7. These three
WSP 6 1.394004 1.440378 1.408995 1.489887 1.232773 1.094808 1.412395 elements were classified in the cause group as directly
WSP 7 1.544473 1.59183 1.561883 1.644705 1.376598 1.33729 1.408416 affecting the others. From the prioritised element, the highest
element is WSP 4 which is manufacturing cost reduction.
The factor was found to be cause when ri – cj was However, this study is relevant to the Malaysia scope as it
positive. Furthermore, when ri – cj was negative the factor is was collected in Malaysia only.

effect [8]. As table 8, WSP 1, WSP 2, WSP 3 and WSP 4 are

factors of effect. Meanwhile, WSP 5, WSP 6 and WSP 7 is

Retrieval Number: D5425118419/2019©BEIESP 11005 Published By:
DOI:10.35940/ijrte.D5425.118419 Blue Eyes Intelligence Engineering
& Sciences Publication

Development of Sustainable Supplier Selection Model using DEMATEL for Manufacturing Industry

ACKNOWLEDGMENT Institute of Technology (MBOT). She is now a Vocational Training Officer
at Majlis Amanah Rakyat.
This research was co-funded by Majlis Amanah Rakyat
(MARA).

REFERENCES

1. R. Geng, S. A. Mansouri, and E. Aktas, “The relationship between

green supply chain management and performance: A meta-analysis of
empirical evidences in Asian emerging economies,” Intern. Journal of
Production Economics, vol. 183, no. October 2016, pp. 245–258, 2017.
2. Q. Zhu, J. Sarkis, and K. Lai, “Green supply chain management:

pressures, practices and performance within the Chinese automobile
industry,” Journal of Cleaner Production, vol. 15, no. 11–12, pp.
1041–1052, Jan. 2007.
3. R. I. Van Hoek, “Research note From reversed logistics to green supply
chains,” 2012.
4. N. Kumar Sahu, S. Datta, and S. Sankar Mahapatra, “Green supplier
appraisement in fuzzy environment,” Benchmarking: An International
Journal, vol. 21, no. 3, pp. 412–429, Apr. 2014.
5. S. Shaw, D. B. Grant, and J. Mangan, “Developing Environmental
Supply Chain Performance Measures,” Benchmarking: An

International Journal, no. June, 2009.
6. I. E. Nielsen, N. Banaeian, P. Golin, H. Mobli, and M. Omid, “Green

Supplier Selection Criteria : From a Literature Review to a Flexible
Framework for Determination of Suitable Criteria,” 2014.

7. F. S. Mohamed Abdel-Basset, Gunasekaran Manogaran, Abduallah
Gamal1, “A hybrid approach of neutrosophic sets and DEMATEL
method for developing supplier selection criteria,” Design Automation

for Embedded Systems, 2018.
8. M. Nazir and N. Cavus, “ScienceDirect Fuzzy DEMATEL method for

identifying LMS evaluation criteria,” Procedia Computer Science, vol.
120, pp. 742–749, 2018.

AUTHORS PROFILE

Norhafiza Binti Mohamed preceived a Bachelor in
Manufacturing Engineering from the Universiti Teknikal
Malaysia Melaka (UTeM) and finished her Master in
Manufacturing System Engineering at Universiti Putra
Malaysia (UPM). Currently, she is pursuing her Ph.D. in
Manufacturing Engineering at the Universiti Teknikal Malaysia Melaka
(UTeM). Her research and publication interests include supply chain
management, operation strategy, and supplier development. She is also
member of the Board of Engineer Malaysia (BEM). She is now a Vocational
Training Officer at Majlis Amanah Rakyat

Associate Professor Ts. Dr. Wan Hasrulnizzam Bin
Wan Mahmood holds a Ph.D. in mechanical and material
engineering by the Universiti Kebangsaan Malaysia
(UKM). He is a senior lecturer in Faculty of Engineering
Technology, Universiti Teknikal Malaysia Melaka (UTeM). The areas of
research that he interests and works on are lean manufacturing, operation
management, quality management and production planning.

Dr.Muhamad Zaki bin Yusup holds a Ph.D. in
Manufacturing engineering by the Universiti Teknikal
Malaysia Melaka (UTeM). The areas of research that he
interests and works on are lean manufacturing, operation
management, quality management and production
planning. He is also member of the Board of Engineer
Malaysia (BEM). He is now a Vocational Training Officer at Majlis Amanah
Rakyat
Rahayu Tukimin received a Bachelor in Electrical
Engineering from the Universiti Malaya (UM) and
finished her Master in Manufacturing System
Engineering at Universiti Putra Malaysia (UPM).
Currently, she is pursuing her Ph.D. in Manufacturing
Engineering at the Universiti Teknikal Malaysia Melaka
(UTeM). Her research and publication interests include supply chain
management, operation strategy, and supplier development. She is also
member of the Board of Engineer Malaysia (BEM) and the Malaysian

Retrieval Number: D5425118419/2019©BEIESP 11006 Published By:
DOI:10.35940/ijrte.D5425.118419 Blue Eyes Intelligence Engineering
& Sciences Publication

International Journal of Recent Technology and Engineering (IJRTE)
ISSN: 2277-3878, Volume-8 Issue-4, November 2019

Prediction of Driver Behaviour in Different
Driving Path by using Electric Buggy Car

Hasri Haris, Wan Khairunizam, Hafiz Halin

 driver habit in term of acceleration and overtake [10]. They
Abstract: Each human has the capability to make decisions and develop a personalized system after analyzing the human
driver‟s various properties such as gender, age, driving
respond to situations completely on its own based on their experience, personality, and emotion. To achieve ideal
intelligence level and experience. During driving, ability makes comfort for passengers, the develop controller need to adapt a
the driver alert and know what they need to do in a certain human-like control method. Artificial intelligence controller
situation. This paper aims to investigate human behaviour while was able to imitate human-like decision-making ability. To
driving the electric vehicle at the desired path. The electric buggy develop human-like controller, preliminary data are gathered.
car is used and set up with equipment and sensor as an Electric The data are analyzed and used to create a Fuzzy controller in
Vehicle (EV). Several sensors used to collect data and certain the future.
criteria subjects are selected with the purpose to study their driving
pattern. The speed, steering wheel angle, heading, and position of The path tracking for autonomous vehicles requires the
the buggy car is collected throughout the human navigation control of the steering wheel in order to follow the selected
experiments. The behaviour of the human while driving in the path [7]–[9]. The point of this examination to build up a
straight path, turn left and turn right will be collected at the end of Fuzzy controller that uses the analysis' information to build up
experiments. the controller for an electric surrey vehicle. The human route
information was utilized to diminish the automated and
Keywords: Human Behaviour, Electric Buggy Car, Electric unnatural inclination as the traveller utilize self-sufficient
Vehicle, Steering Wheel Angle. vehicles. The human route trial is the investigation that
assembles information from the human driver as they pass
I. INTRODUCTION through planned ways. The conduct of the human while
driving in a straight way, turn left and turn right will be
This autonomous driving is progressively pulling in open gathered toward the finish of investigations.
enthusiasm because of different research extends over the
previous years. Generally, regular vehicles were utilized with This paper sorted out as pursues: System Description
huge exertion, and a wide range of sensors set on the rooftop. examines the technique utilized in the examination.
The development of electro-portability gives the opportunity Investigation Setup depicts the human examination
to totally new vehicle ideas. By splitting ceaselessly from arrangement in the exploration. Results and Discussion
great approaches, it is conceivable to consider and introduces the results and dialogues. At last, an end toward the
incorporate self-ruling crashing into the vehicle engineering finish of the paper.
concerning IT and sensor frameworks, vitality the executives
and plan. These sorts of autos are the overhauled variant of II. SYSTEM DESCRIPTION
electric vehicle (EV). As of late a great deal of EVs and
related vehicles, for example, a mixture vehicle has been A. Electric Buggy Car
created to tackle condition and vitality issues brought about
by the utilization of an inner burning motor vehicle. Growing The Yamaha electric buggy car (Figure 1) has chosen to
such vehicles for taking care of nature and vitality issues is an develop an Autonomous Electric Vehicles for this project.
extraordinary thought. Right now, numerous kinds of research The electric buggy car was easier to modified and install with
distribute specialized papers in diaries, which are identified several sensors. It was powered by 48V batteries and
with self-sufficient EV. equipped with an 8.5 kW DC motor for the acceleration. The
specification of the electric buggy car used shown in Table 1.
Decision making important for an autonomous vehicle as it
is decided the safety and comfort of the passenger. In
Malaysia, 80.6% of the fatal road accident caused by human
error [6]. The statistic keeps increasing every year. Lin Li et.
al tried to make an autonomous system to imitate human

Revised Manuscript Received on November 19, 2019 Figure 1: Electric Buggy Car
* Correspondence Author

Hasri Haris, School of Mechatronic Engineering, University Malaysia
Perlis (UniMAP), Perlis, Malaysia / Kolej Kemahiran Tinggi MARA Balik
Pulau, Penang, Malaysia. Email: [email protected]

Wan Khairunizam, School of Mechatronic Engineering, University
Malaysia Perlis (UniMAP), Perlis, Malaysia. Email:
[email protected]

Hafiz Halin, School of Mechatronic Engineering, University Malaysia
Perlis (UniMAP), Perlis, Malaysia. Email: [email protected]

Retrieval Number: D5426118419/2019©BEIESP 11007 Published By:
DOI:10.35940/ijrte.D5426.118419 Blue Eyes Intelligence Engineering
& Sciences Publication