2023 ICPR27 51 Blockchain, IoT, KI und machine learning, digital twin and digital platforms, the findings boost our understanding of the current state of digital technologies in the energy sector. This study set out to gain better insight on prevalent perceptions of the digital technologies in the energy sector to meet decarbonization future goals. The challenges and opportunities of implementing these technologies are highlighted as well as future directions are identified. [7263] INTELIGENT PREDICTIVE MAINTANANCE FOR THE FAULT DIAGNOSIS OF THE ELECTRIC INDUCTION MOTOR Emilia Campean (Technical University of Cluj-Napoca), Claudiu Abrudan (Technical University of Cluj-Napoca) and Mircea Arion (CMAT Industries). Abstract Digitalisation of the industrial activities assures a higher production volume and the exploitation in optimal conditions with high performance of industrial systems These objectives are related with preventing malfunctions caused by faulty equipment. Industrial system digitalisation combines the equipment with facilities like: Internet of Things, Machine Learning, Big Data or Cyber–Physical System. Accidental machinery failure can be eliminated with the help of the new technologies. Fault diagnosis and monitoring conditions have been studied aiming to prevent the occurrence of industrial installations interruption due to engine failure. The paper analysis the trends of industrial maintenance and real-time identification of possible defects in the beginning state of wear. The study analysis the monitor and faults diagnosis of the induction electric motor in order to increase energy efficiency and operational safety using the vibration analysis method. [7273] The value of context in the construction of Storytelling for tacit knowledge management in complex organizations Felisa Córdova (Universidad San Sebastian Chile), Margareth Gutierrez (Universidad San Sebastián, Chile) and Cecilia Montt (University of Santiago de Chile). Abstract This paper analyses the importance and value of the correct definition of the context in the construction of Storytelling, for its application in organizations, as well as a tool to manage knowledge within it. This, because there is a great opportunity in the use of narrative as a mechanism for externalizing tacit knowledge in complex organizations. It describes the emergent property that occurs between the phenomenon or the facts that the subjects live, together with the context relative to the external environment that surrounds the facts. These two elements together make sense of it and bring out the essence of the experience that makes each situation unique. The "butterfly effect" is analyzed, referring to how small variations in the initial conditions of a study have a considerable impact on the expected results. Next, we propose a way to treat the context of a Storytelling applying the methodology of soft systems, from the point of view of the actors, who are those who live the reality of the story and the readers, who face a situation similar to that told in the story, but in different contexts. Finally, the seven phases of the methodology are presented: perception of the unstructured situation/problem, structured perception, elaboration of basic definitions of relevant systems, elaboration and testing of conceptual models, comparison of conceptual models with reality, execution of feasible and desirable changes and implementation of changes in the real world. This journey allows us to face the problem of accurately identifying the real and perceived context in Storytelling and reaching a solution by the reader. [7279] Developing a framework for performance assessment of global distributed teams Joseani Schreiber (PUCPR - Pontifícia Universidade Católica do Paraná), Edson Pinheiro De Lima (UTFPR), Fernando Deschamps (Pontifícia Universidade Católica do Paraná) and Sergio Eduardo Gouvêa da Costa (UTFPR). Abstract Abstract: Virtual teams are considered the answer to many organizational problems today. Advances in information technology, along with competitive pressures, have led to the increasing use of virtual teams for activities as diverse as product development, customer service, systems design and programming, implementation of strategic programs and projects, among others. Despite the fact that research on team performance is increasing on understanding virtual
2023 ICPR27 52 teams, there is still much to be learned in order to fully understand their potential. Performance appraisal is considered a challenging task by many business managers. With virtual team members distributed globally and coming from different cultures and backgrounds, it is important to ensure that the entire performance review process is perceived as fair and correct by all stakeholders. The objective of this study was to build a framework to measure the performance of globally distributed teams. To meet the objective, a systematic review of the literature was sought, in which 76 articles were found, "aspects that hinder and facilitate the development of globally distributed teams" where some criteria were identified that contribute to organizations to evaluate the performance and managing globally distributed teams. The proposed framework was operationalized with the application of the PROMETHEE-ROC method, based on the multicriteria decision support approach, useful in situations where there is inaccurate information related to the importance of the criteria in the decision context. The framework was operationalized in three stages: the presentation of alternatives, the association of alternatives with the criteria and the matrix of consequences. As a result of applying the framework, the ordering of actions to be taken to increase the performance of globally distributed virtual teams was obtained, producing results for the model and for the method (learning of use and application) and also had a relative contribution to the literature of teams distributed in the problem structuring process itself. [7406] Exploring the stability region of engineer-to-orderarchetypes with rework Yuxuan Zhou (Logistics and Operations Management, Cardiff Business School, Cardiff University), Xun Wang (Logistics and Operations Management, Cardiff Business School, Cardiff University), Mohamed Naim (Logistics and Operations Management, Cardiff Business School, Cardiff University) and Jonathan Gosling (Logistics and Operations Management, Cardiff Business School, Cardiff University). Abstract Although engineer-to-order (ETO) supply chains are receiving increasing attention in recent years, there is little research on ETO system dynamics archetypes. This paper aims to enhance an existing design-production ETO archetype with rework (ETOAR#1) recently developed via control theory, but which only focussed on quality issues and rework in the production sub-system. We extend by considering design rework(ETOAR #2) and delayed-detected design rework (ETOAR #3) scenarios. Designrework refers to a scenario that design defects are identified and rectified during the design phase. Delayed-detected design rework refers to the scenario in which faults are detected after production starts and require redesign. The archetypes developed for these two scenarios therefore completes the ETO archetype with rework suite. Using z-transform techniques we derive the stability regions of the three ETOsystemtypes. As a pure delay represents the design and production lead times, we find that high order models are derived that become mathematically and analytically intractable. Thus, this paper adopts three methods to derive the stable boundaries, namely, the RouthHurwitz method for a system whose dimension is lower than four and the hybrid Routh-Hurwitz - Monte Carlo and eigen value analysis methods for systems whose dimension is equal to or higher than four. From a theoretical perspective, this paper contributes to the ETO body of knowledge by providing a completed ETO archetype family with the characterisation of the dynamic properties, and in particular the stability regions, of three types. From a practical standpoint, this research provides a method to assess the total cost implications of the various forms of rework, which includes the direct cost for rectification, and the indirect cost, caused by rework induced dynamics. Furthermore, this research also assists managers by determining model parameter selection for given levels of rework to ensure system stability. [7439] Action plan to prevent fatal road accidents using Data Mining Cecilia Montt (Universidad de Santiago de Chile), Camila Vicencio (Universidad de Santiago de Chile), Luis Quezada (Universidad de Santiago de Chile), Astrid Oddershede (Universidad de Santiago de Chile) and Alejandra Valencia (Pontificia Universidad Catolica de Valparaiso). Abstract This paper develops action plans to prevent fatal accidents in Chile's most populated region, using data mining techniques to characterise them. Despite the increase in population and motorisation rate, accident fatalities have not increased, but have remained constant, indicating that the efforts made in road safety are having an effect, however it is necessary to reduce this figure to a number close to zero fatal accidents. Therefore, the objective of this work is to propose actions to reduce the expected number of fatal accidents, by characterising them. The data of fatal traffic accidents from 2014 to 2019 are analysed, then various neural network architectures were developed, evaluating the
2023 ICPR27 53 performance of these, choosing the one that performs best and applying a relevance analysis of variables, with the Olden method in order to highlight the most influential attributes. The most relevant variables in this study, by intersecting the results obtained from the methods applied, are pedestrians, age range, cause of the accident and time of the accident; these are used to describe proposals to help improve road safety in the country, such as legislation, enforcement and design in favour of traffic calming, road safety education starting with children aged 5 years or younger, and others. [7456] Configuration of machines and a multistep switching policy in dynamic hybrid MTS/MTO production systems. Shohei Kanda (Graduate School of Advanced Science and Engineering, Hiroshima University), Keisuke Nagasawa (Graduate School of Advanced Science and Engineering, Hiroshima University), Katsumi Morikawa (Graduate School of Advanced Science and Engineering, Hiroshima University) and Katsuhiko Takahashi (Graduate School of Advanced Science and Engineering, Hiroshima University). Abstract The hybrid MTS/MTO production system, which consists of make-to-stock (MTS) and make-to-order (MTO) streams in a shared facility, is superior for efficiency and productivity. Notably, in "dynamic" hybrid production systems, two types of machines exist: MTS-dedicated and hybrid machines. Depending on the situation, a hybrid machine can be switched between MTS and MTO production. Zhang et al. (2013) developed a queueing model for a dynamic hybrid production system. They showed high utilization with fewer machines and less cost than the "static" hybrid system (i.e., hybrid system with no switchable machine). However, MTO waiting customers increased due to all the switching hybrid machines altogether (called the "group switching policy"). They also indicated the single switching policy, in which each hybrid machine is switched one by one when hybrid machines are switched from MTS to MTO production, was able to slightly improve system performance compared to group switching policy in the numerical experiments. The research investigates the effective configuration of MTS- and MTO-dedicated machines and hybrid machines under a multistep switching policy where each hybrid machine can be switched stepwise. A hypothesis for a dynamic hybrid production system is provided: MTS demand and production become balanced when some hybrid machines are switched. Therefore, the machines which are unnecessary to switch would be utilized as MTO-dedicated machines so that MTO waiting customers can be reduced preferentially. Numerical experiments demonstrate that the proposed multistep switching policy can be operated more stably at a lower cost than under a group switching policy. Furthermore, MTO waiting customers can be reduced by MTO-dedicated machines while maintaining a lower cost. As one of the operational issues of this system, the amount of calculation increases due to the combination of machines and switch-timing of each hybrid machine. Hence, we propose a fast-search heuristic to obtain approximate optimal operating rules quickly. Numerical experiments show the effectiveness of the proposed heuristic; that is, feasible solutions with lower cost and less amount of calculation compared to previous research and exhaustive search. Reference Zhang Z.G., Kim I., Springer M., Cai G., Yu Y., "Dynamic pooling of make-to-stock and make-to-order operations," International Journal of Production Economics, 2013, 44-56, 144(1). [7516] CHALLENGES AND RESEARCH ISSUES FOR REMANUFACTURING IN PAAS FROM THEORY TO INDUSTRY PERSPECTIVE Paulina Golinska-Dawson (Poznan University of Technology), Tomohiko Sakao (Department of Management and Engineering, Linköping University), Erik Sundin (Department of Management and Engineering, Linköping University) and Karolina Werner-Lewandowska (Poznan University of Technology). Abstract Product-as-a-service (PaaS) is an emerging business model, that supports upscaling of the circular economy in the industries with producer’s extended responsibility. In the PaaS models, the ownership of products stays with a manufacturer, and the functionality of a product is offered to customers for a limited period of time. The successful implementation of PaaS requires multiple uses of products across more than one life cycle. Remanufacturing is vital to bring the return product to conditions that make it attractive to customers in the next PaaS offering. The PaaS business model can make many of the earlier remanufacturing research issues irrelevant (e.g., the uncertainty of incoming cores), and it may enable research to focus on a limited set of issues that are manageable in practice. The purpose of this paper is to present a summary of the literature review on the challenges of remanufacturing in PaaS (product as a service)
2023 ICPR27 54 settings. We identify and assess in a structured way the main challenges that are crucial for upscaling remanufacturing in PaaS settings. We combine the findings of the literature review with the insights of industrial cases. [7533] Open-sorce IIOT operating and control software application for a weld-and-polish robotic cell Mircea Fulea (Technical University of Cluj-Napoca), Cosmin Ioanes (Inno Robotics SRL Cluj-Napoca), Bogdan Mocan (Technical University of Cluj-Napoca) and Mircea Murar (Technical University of Cluj-Napoca). Abstract The ubiquitous connectivity between machines, sensors and actuators, which is the IIoT, is significantly changing how goods are manufactured. It has a great potential to reduce costs, improve production efficiency, and enhance manufacturing and service quality. It also raises challenges for companies, especially for SMEs, like data management or investment costs. In this work we undertake a case study, within a robotic solution integrator SME, which addresses these two issues. We report on designing the information architecture of an OSS-based, IIoT operating and control software application for a weld-and-polish robotic cell, for which we relied on several taxonomies, identified in the literature, related to manufacturing processes. We also report the technical and managerial implications of this technical endeavour, the present case study aiming to serve as a good practice for other SMEs interested in adopting OSS as a backbone of their IIoT applications. [7555] Technology Transfer as an Accelerator of Post-Pandemic Industry Recovery Lisa Craiut (Doctoral School of Engineering Sciences, Department of Engineering and Management, University of Oradea) and Constantin Bungau (Doctoral School of Engineering Sciences, Department of Engineering and Management, University of Oradea). Abstract The present paper evaluates the role of technology transfer (TT) in the post-pandemic recovery of the Romanian industry. It illustrates the current state of the industry in Romania, highlighting the effects of the COVID-19 pandemic in the context of demand shifts, production and operational challenges, supply chain disruptions, labor shortages and financial constraints. It identifies TT as a viable solution and as an accelerator for post-pandemic recovery, considering the need for research, development, and innovation to restart the industry. The paper examines the case of a Romanian production plant and describes various applicability scenarios for TT in a country which has been impacted by the pandemic and is also lagging in industrial performance compared to other European states. [7589] Contributions to the modeling and optimization of data backup solutions within an industrial organization Radu Costin Moisescu (Politehnica University of Bucharest), Constantin Olteanu (Politehnica University of Bucharest), Petrica Tertereanu (Politehnica University of Bucharest) and Aurel Mihail Titu (Lucian Blaga University of Sibiu). Abstract Abstract: In the knowledge-based economy, data is a representative factor for organizations' capital. It can be said that data could represent an important production factor for goods, but especially in the field of digital services. The increase in the volume of data processed within organizations can lead to new challenges in terms of organizational management but also of the methods of optimizing the processes through which data is saved in the backup environments, through which to ensure their recovery in case of disasters. The scientific paper actually presents the way to an evaluation of the possibilities of modeling and optimizing the processes of the data volumes backup from the perspective of implementing the provisions of the ISO27001:2018 security standard. The scientific work is based on applied research and can represent a well-argued point of view of the authors regarding the backup technologies with applicability in industrial organizations.
2023 ICPR27 55 [7628] Multi-factory scheduling for a corporated supply chain Yuusaku Tahara (University of Tsukuba), Yasutomo Nagai (University of Tsukuba) and Sumika Arima (University of Tsukuba). Abstract This paper introduces the n-step hybrid flow-shop scheduling (nHFS) for a corporated supply chain in which component assembly and final assembly factories are linked in series (tandem-type). We applied n-GuptaEX=SETUPBO method(Mao et.al., 2022) which is advanced form of one of representative nHFS solution proposed by J.N.D Gupta et.al. (2002). As a baseline, n-GuptaEX=SETUPBO method improved both the optimization level and the computational efficiency much in our previous study. Now, for the case of multi-factory, each factory has a different utility, and there is a trade-off relationship between them. The purpose of this study is to improve the performance of the entire supply chain through integrated scheduling that balance the interests of each factory. Its scheduling performance is evaluated by comparing it to other existing approaches. Discrete event simulation is used in numerical experiments. [7710] Co-located collaborative Virtual Reality to accelerate the engineering process Benjamin Wingert (Fraunhofer IAO), Jan Hofmann (Universität Stuttgart), Matthias Bues (Fraunhofer IAO) and Oliver Riedel (Fraunhofer IAO). Abstract Collaboration is vital in product development, involving stakeholders from various disciplines, teams, locations, and management levels. Virtual reality (VR) systems can optimally support collaboration in various stages of the product development process, particularly for tasks like CAD review. VR goggles and multi-viewer powerwalls both enable collaborative CAD reviews, with multi-viewer powerwalls offering multiple 3D perspectives. However, both technologies have their advantages and disadvantages. A key distinction is that multi-viewer powerwalls allow people to see each other in reality, while VR goggles use virtual avatars lacking facial expressions and gestures, strongly limiting communication in co-located scenarios. This paper explores the suitability of VR goggles and multi-viewer powerwalls for collaborative CAD review, comparing their advantages and disadvantages through a qualitative user study. Results show that multi-viewer powerwalls, such as the CoLEDWall, significantly enhance communication and teamwork, fostering more intensive collaboration in the product development process, surpassing the currently predominant use of VR goggles. [8002] SOME SIGNIFICANT MOMENTS AND SPECIFIC NATIONAL APPROACHES TO CONSUMER PROTECTION AROUND THE WORLD Mircea Radu (UTCN Cluj-Napoca). Abstract The paper aims to identify from the literature and reliable sources on the web and to present in a sintetic manner some aspects and time moments of consumer protection concerns, respectively their specific approaches in diferent countries of the world. As background, the definitions and content for few basic concepts of customer protection and their variations are summarised. After the brief presentation of some very early historical milestones, the paper focuses on the modern industrial era reviewing few landmarks concernning the recent history and present status of the national or transnational institutional approaches. [8061] On the development and initial validation of WisdomOfAge - a matchmaking mentoring platform for sustainable development Gabriela Rus (CESTER (Technical University of Cluj-Napoca)), Calin Vaida (Technical University of Cluj-Napoca), Bogdan Gherman (Technical University of Cluj-Napoca), Adrian Pisla (Technical University of Cluj-Napoca), Laurentiu Nae (Digital Twin), Paul Tucan (Technical University of Cluj-Napoca), Doina Pisla (Technical University of Cluj-Napoca) and Mihai Ciupe (CESTER, Technical University of Cluj-Napoca, Memorandumului 28, Cluj-Napoca, Romania).
2023 ICPR27 56 Abstract The paper focuses on the development of a matchmaking platform targeting the externalization of high-level and specific activities within the industrial design sector by providing access to expert advice from experienced senior engineers. Recent events in our society, such as the Covid-19 pandemic, pointed out a series of complex problems in many sectors, where human factors represent the central point. The main challenge these sectors must face is the scarcity of qualified human resources, resulting from the fast-aging population, inability to recruit competent resources, or incapability to keep a person for a long period of time. Considering these aspects, one of the most affected sectors is industry, where the lack of experts often caused disruption of the supply chains. Thus, this paper aims to respond to the scarcity of experts in this area, providing an analysis of a possible solution, taking into account the requirements of the industry companies. The proposed mentoring platform focuses on providing capable experts to companies, able to respond to a specific problem in an efficient way, considering that experts are seniors, who have been working in the industry for a long time. This becomes achievable through a matchmaking system that is able to link a senior profile with the stated problem submitted by the companies’ representatives powered by artificial intelligence agents, ensuring that the selection process becomes more accurate as the platform is used more often. Some initial results are presented, validating the concept before the market launch. [8088] Enhancing CNC Milling Machine Operator Training with Augmented Reality Smart Glasses Emilia Brad (Technical University of Cluj-Napoca), Vladut Trifan (Technical University of Cluj-Napoca), Dragos Bartos (Technical University of Cluj-Napoca), Ionut Chis (Technical University of Cluj-Napoca) and Anca Stan (Technical University of Cluj-Napoca). Abstract The rapidly evolving field of Augmented Reality (AR) technology offers significant potential to revolutionize traditional training methods in various industries. This study investigates the use of AR, specifically smart glasses, to improve the training efficiency and performance of CNC milling machine operators. The research question seeks to understand how the integration of AR technology in the form of smart glasses can enhance the learning process and optimize the overall training experience for CNC milling machine operators. Our methodology involves a comprehensive approach to developing, testing, and improving an AR application tailored for CNC milling machine operation, seamlessly integrated with smart glasses. The application utilizes advanced AR technologies, such as real-time information display and contextsensitive assistance, to provide an immersive learning experience. A sample group of trainees participates in a controlled study to evaluate the effectiveness of AR-assisted training in comparison to traditional training methods. Quantitative data analysis reveals a 30% improvement in training efficiency and a 25% reduction in the training period, leading to enhanced operator performance and reduced error rates. A thorough discussion of these findings evaluates their implications for CNC milling machine training, including the advantages and limitations of the AR-assisted approach, as well as recommendations for future research to further explore the potential of AR in industrial training contexts. A thorough discussion of these findings evaluates their implications for CNC milling machine training, study limitations, and recommendations for future research. [8091] EU carbon border adjustment mechanism under economies of scale Tanzin Ahmed (Aalto University) and Esko Niemi (Aalto University). Abstract As part of the European green deal European Union (EU) has proposed Carbon Border adjustment mechanism (CBAM). Its purpose is to compensate for emission taxes within EU to avoid carbon leakage to non-taxing countries. Among all possible options, border tariffs for products imported from non-taxing countries to EU countries are set equal to emission taxes. This appears fair, but the economies of scale effects are not considered. This paper examines the effects of realistic cost functions on the resulting production allocation. We experiment with single product, four-country, equilibrium model where three countries are potential producers, and all four countries are markets. In our model, demand and supply (producer cost) function parameter values and transportation cost are equal, and total producer profit is maximized. Our cost function is a power curve entailing economies of scale. We primarily examine the effects of producer tax and border tariff levels on production and profit. We also consider the effect of consumer tax during
2023 ICPR27 57 experimentation. The results show that the amount of economies of scale strongly affects the profit-maximizing production allocation. It appears that under economies of scale effects the EU border tariff levels are far too low to create a fair marketplace. Low border tariffs under economies of scale lead to centralized production by a non-taxed producer using polluting technology, whereas sufficiently large border tariffs decentralize production to different countries, and the amount of polluting production is reduced significantly. The effects of short-run capacity constraints and market size on the production allocation are also examined. [8230] Tailored Adaptive Large Neighborhood Search to optimize a real-world logistic service for dependent patients Francesco Pilati (University of Trento), Riccardo Tronconi (University of Trento) and Karl Doerner (University of Vienna). Abstract In recent years, the number of disabled people has been growing drastically due to both the increase in the people age and non-communicable disease. This trend makes the existing healthcare logistic services inadequate to meet patients demand and, thus, a model to improve the efficiency of this service, which in scientific literature is called Dial-a-Ride problem (DARP), is necessary. Furthermore, in this kind of problems the human factor is relevant but it is usually hardly measurable since there is no standard quantitative parameter. To fulfill this need, the goal of this research is the development of a metaheuristic algorithm to solve a real-world static DARP with homogeneous requests and a single depot, aiming at optimizing the logistic service for dependent patients. Indeed, this paper presents the implementation of an Adaptive Large Neighborhood Search (ALNS) algorithm with some destroy and repair operators tailored for the targeted problem to reach a high-quality solution in an acceptable time consistent with the need of a real healthcare department. This metaheuristic algorithm is compared with the current benchmark in literature and it is validated in a real-world case study of the Austrian Red Cross to observe how the algorithm works with real parameters and constraints. Results show that the developed ALNS is distinguished by performances comparable to the benchmark for all the tested instances. Moreover, this paper reports different Key Performance Indicators about the logistic service. First of all, it presents how the selection probability of each destroy-repair operators pair adapts along the iterations according to their past performance. Secondly, some results are provided regarding the social sustainability aspects of the logistic service, in terms of minimization of patients inconvenience and drivers satisfaction, such as patients waiting time and total time worked. [8273] PERFORMANCE ANALYSIS OF THE ORGAN DONATION AND TRANSPLANT PROCESS WITH PROCESS MINING Letícia Faria Moura (Cefet/RJ), Rafael Paim Cunha Santos (Cefet/RJ), Laís Fonsêca (Central Estadual de Transplantes), Alexandre Cauduro (Central Estadual de Transplantes), Priscila Paura (Central Estadual de Transplantes) and Claudia Araujo (COPPEAD - UFRJ). Abstract Process mining (PM) has been evolving from a process and data science topic to a useful technology related to production research. Process discovery, conformance checking, and enhancements are PM techniques used to improve performance. In health services, the hospital, health production systems, and society benefit from PM tools and techniques utilization in order to generate value. The research aimed to analyze the process design, data and indicators applying PM techniques and using the Celonis tool, considering as the object the donation for transplantation process in Rio de Janeiro, using 2021 data. The research was motivated by low performance when comparing this state to benchmarks. The methodology was based on the design research method with a bibliographical review, PM tools selection, data preparation, and interviews to identify improvements. With the study, it was possible to demonstrate applicability of PM and an increase in organ donations was observed.
2023 ICPR27 58 [8298] Modeling the paradigm shift towards renewable energy sources in the Mauritian Textile & Apparel Industry using System Dynamics Devkumar S Callychurn (University of Mauritius). Abstract Purpose The energy sector in Mauritius has been classified as a major pacesetter for the social and economic development of the country. Given the limited known exploitable energy sources, and deprivation of oil, natural gas, or coal reserves, the island depends exclusively on imported petroleum products to meet most of its energy requirements. Among these, coal and oil play a significant role and are the most dominant sources of energy. This is bound to be threatened by the declining stocks of fossil fuels and ever-increasing prices and high cost of transportation which makes the importation process very expensive. Coupled with that is the ever-increasing pressure of having the protection of the environment high on the agenda. This is even more pressing for the Textile & Apparel Industry in Mauritius since much if not all of its operations are energy-dependent. This research work investigates how to devise sustainable and renewable strategies as far as energy is concerned, most specifically for the textile and apparel industry. The end result is the development of a decision support system that could be used for the greening of the textile apparel industry with regard to energy utilization. The resulting framework enables companies to identify and develop the competencies that will determine the nature and type of flexibility required to respond to the scale and pace of change that businesses will encounter over the next forty to fifty years. Design/Methodology/Approach This research investigates the impact of having various additional sources of renewable energies such as hydro, wastes to energy, wind, and solar PV as new sources for the Textile & Apparel industry in Mauritius. An AS-IS model was developed using the STELLA Modeling Software. This base model was used as base one for meditation with experts in the field to look at the possibility of going for other more renewable energy sources for greening the textile and apparel industry in Mauritius. The findings of the various meetings and discussion sessions were of great help to come up with a TO-BE model for the industry. The model focuses a lot on the potentiality of using renewable energy sources such as solar, wind, hydro, bagasse, and bamboo, among others. Energy production from solid wastes, as well as landfill gases, is also considered. In fact, it has become pressing that the reliance on fossil fuels recede. There should be an effort to increase the production of electricity from renewable sources and supply the energy to the national electricity grid. The most important components that have been considered while working out the model are as follows: • Energy from hydro, solar and wind • Energy from petroleum products • Energy from bamboo and bagasse • Energy from solid wastes through landfills Findings The model for the future and greener textile and apparel industry gave a novel and different perspective to the stakeholders about the strategy to adopt in the future, as far as the utilization of energy was concerned. It becomes imperative to capitalize on the natural resources that are available in Mauritius in the quest to be more sustainable. Even more so when other resources are becoming more and more expensive. This research has provided various points to ponder by the stakeholders of the industry as well as the decision and policymakers of the country. The main concern remains the provision of land to support the development of wind farms, solar farms, and the production of bamboo and bagasse. One possible solution, as modeled in this research work, is to take 20% of the land currently occupied by sugar cane plantations, which in return is on the decline. This will not only help reduce the dependency on non-renewable energy sources but also could the inception of a new industry. Hence, the creation of more direct and indirect jobs leading to a decrease in the unemployment rate. Last but not the least, this research encourages using Circular Economy in the production of energy by the industry. However, it is deemed important to work on designs, processes, and solutions that maximize the efficient use of natural resources for energy production, end use of energy, excess energ,y and side streams. To be successful in the route towards implementing successful strategies, stakeholders or energy producers need to develop tactics in line with CE, as shown in the proposed energy chain below. Figure 1: Energy value chain and tactics for the Mauritian Textile and Apparel Industry It is worthwhile for the stakeholders to start working on strategies to go towards a detachment from fossil fuels for both climate mitigation and CE in the industry, with regard to energy consumption. However, this requires a systemic change and the industry must start thinking outside the box. On a practical level, textile companies can embark on generating their own renewable energy so that they become self-sufficient. Relevance/Contribution This research paper highlights the importance to shift from conventional energy sources to renewable sources such as hydro, solar, wind, and waste to energy, bamboo, and bagasse, among others. This paradigm shift will however face many challenges in the implementation of the new energy strategies. This will definitely require a systemic change and it’s high time that the main players and stakeholders of the textile and apparel industry in Mauritius
2023 ICPR27 59 start thinking outside the box and their comfort zone. References Alayon.C.L.; Safsten, K.; Johansson,G.;, 2022. Barriers and enablers for the adoption of sustainable manufacturing by manufacturing SMEs. Sustainability 2022, 14,2364. Arnold, R.D.; Wade, J.;, 2015. A Definition of Systems Thinking: A Systems Approach. Castle Point on Hudson,, 2015 Conference on Systems Engineering Research CSO, 2017. s.l.: Central Statistics Office. Fletcher, K.;, 2008. Sustainable Fashion and Textiles: Design Journeys. London: Earthscan. Yip, W.S.; To,S.;,2021. Identification of stakeholder related barriers in sustainable manufacturing using social network analysis. Sustainable Production and Consumption, 27(2021), pp 1903-1917 [8301] Enhanced DDMRP Scheduling Model Incorporating Capacity Constraints and Machine Utilization for Large-scale Manufacturing System Gang Ma (Aalborg University) and Charles Møller (Aarhus University). Abstract Demand Driven Material Requirement Planning (DDMRP) has emerged as a promising approach for managing supply chain complexity and variability. Existing research on DDMRP has focused on simulation models that can accommodate limited numbers of products, with data not originating from real-world manufacturing settings. This study presents an enhanced DDMRP planning model capable of handling more than 170 products, incorporating factory capacity constraints and machine utilization. The proposed model is designed to manage DDMRP-generated production orders effectively, facilitating better scheduling decisions in large-scale manufacturing systems. Utilizing actual data from a manufacturing company, the model’s performance is compared to that of the traditional MRP method in terms of service level. The results indicate that the enhanced DDMRP scheduling model leads to improved supply chain performance, suggesting its potential for widespread application in diverse manufacturing contexts. [8493] Leveraging customer usage data for optimal maintenance policies in product-as-aservice Johan Vogt Duberg (Department of Management and Engineering, Linköping University) and Ou Tang (Department of Management and Engineering, Linköping University). Abstract Maintenance aims to ensure the availability and reliability of equipment so that production processes keep operations, and products sustain with good qualities. However, maintenance decisions rely essentially on the distribution of product’s lifetime. For instance, professional users may use machine tools intensively, whereas as hobby users, the usage of same tools is much less frequent. This variability poses a challenge for companies when adopting product-service offerings, as the maintenance policies should differ to minimise the number of unexpected failures as well as the product life cycle usage costs. This study investigates the identification of customer usage behaviour groups in mixed Weibull distributed product failure datasets. The study proposes an algorithmic model using the Weibull moments to distinguish the underlying Weibull distribution in a mixed distribution. The developed knowledge defines whether customer usage data needs to be distinguished between groups. [8523] Reverse Engineering: The Other Side of Additive Manufacturing Zhaohui Geng (The University of Texas Rio Grande Valley), Bopaya Bidanda (University of Pittsburgh) and Sachithra Karunathilake (The University of Texas Rio Grande Valley). Abstract The technological advancement of additive manufacturing (AM) provides opportunities for flexible designs for critical applications, energy efficiency for low-volume-high-mix production, and sustainability, which revolutionize the manufacturing industry. On the other hand, reverse engineering (RE), a digitization technology that transforms a physical object into a digital design, could generate the input and plan the manufacturing process for AM. The use of RE could
2023 ICPR27 60 facilitate a more efficient solution for increasingly flexible design for AM and, even more importantly, improve the quality of AM-created parts through understanding the manufacturing signatures and patterns through the extracted digital models. Furthermore, adopting both technologies could also benefit the remanufacturing industry significantly through efficient repair solutions and design for sustainability. Focusing on RE will allow the AM to move from custom, prototype production into small batch manufacturing and will represent a significant breakthrough in the type of production. This paper presents an overview of the technology and the major advancements in the RE field, together with its representative applications. Challenges and opportunities in RE will be shared. Two points of view of RE are summarized and discussed, i.e., a design-information extraction technology and a measurement system. These two views disclose different considerations and research focuses in state-of-the-art RE studies. Critical research gaps and working directions are identified and discussed to increase the quality and productivity when using the RE for AM processes. [8568] CARBON FOOTPRINT CALCULATION IN DIFFERENT AREAS OF ACTIVITY DEPENDING ON SPECIFIC EMISSION FACTORS Andreea Ungureanu (Politehnica University of Bucharest), Aurel Mihail Titu (Lucian Blaga University of Sibiu), Madalina Pana (Politehnica University of Bucharest), Iuliana Moisescu (Politehnica University of Bucharest) and Madalina Nita (Politehnica University of Bucharest). Abstract Carbon footprint refers to the total amount of CO2 and other greenhouse gas emissions directly and indirectly caused by a product or activity or associated with the activities of a person or an organization. The key factors influencing carbon emissions are population, economic production, industrial institutions, intensity and structure of energy consumption. Currently, there are no mandatory EU rules for calculating the carbon footprint, so reporting is often carried out superficially or without taking into account all the indirect emissions of organizations. The carbon footprint corresponds to the total amount of greenhouse gas emissions directly and indirectly associated with an organization's activities, therefore the European objectives cannot be fully measured if not all these emissions are included in the calculation. Until the year 2030, the European Commission has proposed the objective of reducing the carbon footprint by 40% compared to the year 1990. Lately, there have been intense concerns from the EU institutions and bodies in environmental issues, many of them joining the Eco-Management and Audit Scheme (EMAS) and other environmental initiatives. This paper aims to present a simplified way of calculating the carbon footprint in different types of organizations, taking into account that depending on the activity carried out, various fuels are used, with distinct emission factors associated with them, following the impact they have on the environment. Attention is also drawn to the need for increasing the level of population awareness in a current subject whose approach cannot be delayed. [8666] TWO WORLDS APART? OVERCOMING THE DISCORD IN TALENT MANAGEMENT BETWEEN ACADEMIA AND BUSINESS Dana Fatol (Politehnica University Timisoara) and Diana Robescu (Politehnica University Timisoara). Abstract This paper investigates the persistent gap between academic research on Talent Management (TM) and its practical application in the business area. Key disparities include differing priorities, with academia emphasizing theoretical advancement and businesses focusing on practical outcomes, where the faster pace of business publications exceeds the typically longer academic publishing process. The paper argues for increased academic-practitioner collaboration, proposing real-world testing of interventions and reciprocal feedback mechanisms to enhance understanding and relevance of academic research, thereby fostering more effective human resources strategies, aiming to align TM research with real-world needs. [8688] Unlocking Innovation: A Pathway to Success for Early-Stage Ventures Jelena Borocki (University of Novi Sad, Faculty of Technical Sciences), Vladimir Djakovic (University of Novi Sad, Faculty of Technical Sciences), Aleksandar Vekic (University of Novi Sad, Faculty of Technical Sciences) and Olivera Cikota (University of Novi Sad, Faculty of Technical Sciences).
2023 ICPR27 61 Abstract Innovation is crucial for the survival, resilience, and success of early-stage ventures in a complex market. It enables them to develop new products, services, and business models that meet customer needs and create value. Encouraging and supporting innovation by startup companies is essential to foster economic growth and progress in various industries. However, innovation is a complex and challenging process that requires significant resources, including financial, human, and technological. Through a comprehensive literature review and research involving startup founders, we identify key factors that facilitate effective innovation in early-stage ventures. These include creating a culture of innovation that encourages creativity and experimentation, leveraging technology to streamline innovation, collaborating with external partners such as universities, research institutions, and accelerators, and securing funding from various sources, including government grants, venture capitalists, and angel investors. Our findings contribute to understanding the challenges and opportunities in pursuing innovation for early-stage ventures, with practical implications for entrepreneurs, policymakers, and investors in this field. [8811] A model for selecting the trajectory of the transformation of the production cell. Marek Fertsch (Politechnika Poznańska). Abstract The paper assumes the continuity of development of production systems, from the beginning of their creation to the model presented by industry 4.0. Accepting this hypothesis, the recommendations on how to move in the shortest possible time and at the lowest possible cost from the current state that can correspond to each generation of production system models to the optimal level, which currently corresponds to the industry 4.0 model are formulated. The analysis is carried out from the point of view of the engineering industry, that supplies the rest of the production industry. At the same time the analyzed industry is characterized by the most complicated production and organizational conditions. The analysis does not refer to the conditions of high-tech manufacturing or the automotive industry. Those industries have developed their own practices in the organization of production. It also does not apply to the conditions of industries such as the food, chemical or clothing industry, in which the specificity of the processed materials and technologies determines the organization of production. [8854] Integration of Collaborative Robots in the Automotive Industry during Post-Pandemic Recovery Aurel Mihail Titu (Lucian Blaga University of Sibiu), Vasile Gusan (Politehnica University of Bucharest) and Mihai Dragomir (Technical University of Cluj-Napoca). Abstract In the era of speed and technological advancement, the automotive industry has faced various crises, pandemics, and catastrophes. Following the global financial crisis of 2008, also known as the Great Recession, the industry was forced to confront the COVID-19 pandemic, and now the entire market is directly facing the semiconductor crisis. Globally, there have been and will certainly be crises regarding human resources, and situations in which global industrial organizations in the automotive sector will face challenges and must implement solutions to optimize their costs to ensure profitability even in times of crisis. In the current conditions, the authors argue that only industrial organizations that are oriented towards flexibility and openness to adaptability will be able to successfully survive. In this context, collaborative robots are becoming an increasingly viable alternative. In this scientific paper, the authors propose a pragmatic vision regarding the integration of collaborative robots, emphasizing the importance of an effective integration process of collaborative robots in organizations within the automotive industry. The authors consider this proposed desideratum an important aspect, as collaborative robots are considered universal and highly flexible tools that can easily adapt to any process.
2023 ICPR27 62 [8951] A methodology for intuitive use of AI-driven solutions in optimisation of manufacturing processes Hendrik von Linde (Fraunhofer IAO, Fraunhofer Institute for Industrial Engineering) and Oliver Riedel (Fraunhofer IAO, Fraunhofer Institute for Industrial Engineering). Abstract The barrier raised by the complexity of AI methods with the intention to optimise manufacturing processes can be overcome by the development of a methodology for intuitive use of complex AI-driven solutions. The developed methodology, with data sourced from real production, aims to support the interdisciplinary end users, e. g. engineers, without any domain expertise. It is also independent from the disciplinary core competences of the manufacturer with a strong focus on employability in small and medium enterprises (SME). This paper describes a methodology for intuitive use of AI-driven solutions in optimization of manufacturing processes. The developed methodology aims to support the interdisciplinary users, e. g. engineers, without any or little domain expertise. It is also independent from the disciplinary core competences of the manufacturer with a strong focus on employability in small and medium enterprises. Described is the foundation of the methodology to evaluate the combination of the two machine learning classes. With a focus on a range of feature selection methods and cluster methods, their limitations, and their challenges. The paper covers the concept phase by defining the inputs - such as the specific characteristics of machine learning classes or the properties of the production data - and identify the user preferences. With applied methodologies such as the Analytic Hierarchy Process or the Technique for Order of Preference by Similarity to Ideal Solution the requirements of the user as valid input are integrated. [9139] Gender diversity issues in logistics and supply chain management: a systematic literature review Biao Yang (University of Sussex Business School), Nachiappan Subramanian (University of Sussex Business School) and Shaima Al Harthy (University of Sussex Business School). Abstract In view of the growing importance of the social aspect of sustainable supply chain management, including gender diversity (GD) issues, this study systematically reviews the literature to determine the current situation of the GD in the supply chain. Forty-nine peer-reviewed articles were selected in this study. Following content analysis, the selected studies are classified and analysed. The study points out four major gaps in the literature and develops a research framework. [9199] Developing dispatching rules for flexible flowshop scheduling problem Feng Yu Hsieh (Feng Chia University), Yang Kuei Lin (Feng Chia University) and Yi Chi Wang (Feng Chia University). Abstract Steel balls are widely used in daily life and industrial applications. The demand for steel balls is consistently high, but the supply often fails to meet this demand. The steel ball manufacturer is constantly seeking ways to maximize machine utilization, increase output, and minimize the number of delayed jobs. In this research, we are collaborating with a professional ball manufacturing company in Taiwan. The ball manufacturing production flow consists of eight sequential stages, with each stage having m identical parallel machines. This setup belongs to a flexible flowshop environment. Most flexible flowshop scheduling problems are known to be NP-hard. The objective function we aim to minimize is the total weight tardiness. We first extract the ordering data from the company's ERP (Enterprise Resource Planning) system. Next, we manipulate and format the data appropriately so that it can be directly fed into our system. For each order, we calculate a score based on factors such as customer priority, order size, due date, and order profitability. This score determines the priority of the order. We then propose four dispatching rules to assign orders to machines at each stage based on their priority. Computational results indicate that the proposed dispatching rules can yield promising results for the studied problem.
2023 ICPR27 63 [9200] Digital Technology Resources and Leadership: Impact on Enabling Capabilities and Performance in Supply Chains Jukka Hallikas (LUT University), Aleksi Harju (LUT Business School) and Mika Immonen (LUT University). Abstract Companies have utilized digitization to achieve a wide range of supply chain-related goals. Technological resources and factors supporting the organization's leadership and strategy have been considered enablers of digitization. Examining the combined effect of these factors gives a new understanding to existing research on the effect of different strategy profiles on the possibilities of information utilization practices and supply chain performance. In this study, empirical survey data (n=129) has been collected from medium-sized and large companies. Based on their technology maturity and digitalization leadership, the respondent companies have been classified by cluster analysis into three strategy categories, the differences between which are supported by the survey data. Based on the preliminary results, it can be said that companies with a high degree of digitalization technology and management maturity are able to create better capabilities for data collection, information sharing and data analytics. These companies also perform statistically better in terms of agility. [9212] Recent robotic research and development trends Ran Shneor (Ben-Gurion University of the Negev) and Yael Edan (Ben-Gurion University of the Negev). Abstract Robotics research is advancing at an increased pace. The global Covid-19 pandemic further increased the need for robotization of processes worldwide. This work aimed to characterise recent trends in robotics research and development (R&D) to direct efforts both in academia and industry. Emerging and declining hot topics were identified by a quantitative and qualitative analysis of scientific sources and reports from the International Federation of Robotics (IFR) and a bibliometric analysis of keywords co-occurrence in leading robotic conferences. Two-time frames (2010-2011, 2020-2021) were compared using the VOSviewer tool. Major increases, decreases, and new entries of robotic topics were identified, leading to the establishment of a keywords chart comparing trends between the two periods. Word clouds analysis was conducted on reports by IFR. The main findings from the keywords chart indicate that artificial intelligence and human-robot interaction (HRI) are major trends. A decrease in tangible keywords (e.g., "locomotion") was identified along with an increase in "equationless" and less tangible keywords (e.g., "social robotics"). The IFR sources pinpointed additional trends (e.g., "semantic intelligence" and "swarm robotics"). The combination of scientific and representative market data sources highlights robotic R&D trends from different perspectives. In the future, more sources (e.g., patents) and text-mining techniques should be added to identify additional trends in robotics. [9323] Cognitive Digital Twins: Approach, Development, and Prototyping in a Discrete Automotive Manufacturing Scenario Stefan Giosan (Fraunhofer Institute for Industrial Engineering - FhG IAO), Carmen Constantinescu (Fraunhofer Institute for Industrial Engineering - FhG IAO) and Daniela Popescu (Technical University of Cluj-Napoca). Abstract The concept of Digital Twin has been widely used in manufacturing industry to enhance product and production quality, reduce costs, and enable manufacturing excellence to prove efficiency and reduce downtime. Coping with unexpected internal and/or external disruptions induces limitations of employing traditional Digital Twins. The authors address these limitations by employing artificial intelligence and machine learning techniques to enhance the Digital Twins with resilience and adaptability features, further on, so-called Cognitive Digital Twins. This enhancement is realized by capturing in Real-Time the critical production parameter from the manufacturing environment as a base for complex simulation and optimization processes. This work presents our approach to a Cognitive Digital Twin, the development methodology, and its prototyping in an automation production scenario focused on the quality measuring process of complex parts in the automotive industry. The conclusions reveal identified barriers, highlight the Cognitive Digital Twins
2023 ICPR27 64 economics, and propose a migration plan in several industries and manufacturing enterprises with a focus on discrete manufacturing and SMEs. [9329] Integrating lot-sizing environmental factors estimation for a green reorder-level inventory control policy Francesco Pilati (University of Trento), Marco Giacomelli (University of Trento) and Matteo Brunelli (University of Trento). Abstract With the aim of reducing pollution as firms start to consider environmental issues, this work focuses on the modeling and optimization of a sustainable reorder-level lot-sizing policy that integrates a tailored estimation of environmental factors for comprehensive green inventory control. In particular, the goal is to minimize total greenhouse gas emissions by modeling the impact of warehousing and resupply of each order quantity. Other than operational aspects that include energy usage for lighting, and thermal control inside a warehouse, building characterization and the related embodied carbon are other often-neglected significant sources of greenhouse gas emissions. This integrated approach allows, in a lost-sales setting constrained by minimal service level, to model the direct relation between emission components and the environmental impact of managing the inventory of a product, which carries clear valuable managerial insights. [9353] The role of Environmental Management Systems (EMS) and Energy Management Systems (EnMS) in the adoption of Energy Efficiency Technologies (EETs) in manufacturing companies in Central Europe Juraj Šebo (Technical University of Košice), Jasna Prester (University of Zagreb) and Miriam Šebová (Technical University of Košice). Abstract The diffusion of technologies within an economic system is a complex process, influenced by various factors including governmental policies, characteristics of adopting companies, adoptable technologies, etc. This study aims to investigate the current state of adoption of Energy Efficiency Technologies (EETs) in central European countries (Croatia, Slovenia, Austria, Slovakia, Lithuania), and identify any prevailing trends and evidence regarding adoption patterns and firmspecific characteristics. Our research utilizes data from the European Manufacturing Survey (EMSurvey) and employs a two-step Ordinary Least Squares (OLS) regression analysis. While our analysis reveals significant relations and differences in the case of EMS, a further examination of the implementation years leads us to the conclusion that it is highly unlikely for EMS or EnMS to facilitate the adoption of Energy Recuperation Technologies [9382] Continuously integrated product design, process, and production optimization. Motivation scenario and prototype: Modular and smart 3D-printed gripper for flexible pickand-place processes Raul Matei (Fraunhofer Institute for Industrial Engineering - FhG IAO), Andrei Fagaras (Fraunhofer Institute for Industrial Engineering - FhG IAO), Carmen Constantinescu (Fraunhofer Institute for Industrial Engineering - FhG IAO), Ralf Lossack (Siemens), Dennis Nier (Siemens), Alexander Stumm (Siemens) and Steffen Kappes (FARO Technologies, Inc. (FARO Europe GmbH)). Abstract This paper presents our approach for development and validation of continuous product optimization, with focus on an automated pick-and-place process with integrated 3D scanning for dimensional and quality measurement. The validation of our approach in an industrial experimental set-up has as a reference product a modular gripper adaptable for a large variant of complex products and having as its main functionality the pick-and-place operation. The developed methodology consists of three phases: 1) Automated topology-driven product design and realization with additive manufacturing technology; 2) Product implementation and testing in a pick-and-place industrial process; 3) Analysis of
2023 ICPR27 65 the experimental results and elaboration of product optimization measures. The approach integrates innovative state-ofthe-art product design, combined with advanced simulation technologies and systems, as well as additive manufacturing. The core of this research is represented by a modular generative design approach and optimization functionality through digital twins and end-to-end simulation. Implementation and validation are crucial for future reference, showing the applicability to any experimental product that requires modular design and incremental improvement in relation to critical manufacturing parameters. [9407] Implementation of Value Stream Mapping and Mathematical Model for Patient Scheduling in Radiotherapy Treatment Wapee Manopiniwes (Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University), Takashi Irohara (Faculty of Science and Technology, Sophia University), Wannapha Nobnop (Division of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chiang Mai University) and Pooriwat Muangwong (Division of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chiang Mai University). Abstract This paper is based on the improvement of patient scheduling in radiotherapy department. We started with the application of Value Stream Mapping (VSM) to the entire patient flow in curative cases. The scheduling plan in radiotherapy treatment is necessary for curative cases, whereas in the palliative cases, it may not be required to the same extent. The VSM analysis of the patient scheduling process revealed that there are several operations in the process that are causing delays. The patients are waiting too long to get into a number of treatments called fractions. In this context, VSM can be used to map out the operations involved in the patient scheduling process as well as identify any bottlenecks or inefficiencies. As a solution, we optimized the scheduling plan, through linear programming, thereby synchronizing CT-simulation, contouring, planning, plan approve, and treatment operations of radiotherapy care. The goal of our formulation was to find the optimal patient schedule that minimizes the maximum completion time across all patients, while also factoring in a penalty score. [9418] The implications imposed by prescriptive maintenance implementation into the Industry 4.0 - a current state analysis Ana-Diana Pop-Suărășan (Technical University of Cluj Napoca) and Nicolae Stelian Ungureanu (Technical University of Cluj Napoca). Abstract In the context of an information technology era, digitalization and a fulminant technological evolution, the prescriptive maintenance occupies a crucial place for increased automation and continuous improvement processes. The concepts and technologies of Industry 4.0 can be applied to various industrial models, starting from the production line and continuing to the decision-making act. The automation, design and operationalization of maintenance plans are becoming more and more effective due to technologies based on the processing of the Artificial Intelligence’s machine learning algorithms. Concretely, we will address a method in which an innovative maintenance strategy, such as the prescriptive one, can influence the organizational development. The predictability, the visibility and the efficiency of the prescriptive analytics and the use of technologies such as the Internet of Things and Big Data provide an improved interconnectivity between systems. Thus, we aim to achieve a strategy to determine the manner and application degree in which the prescriptive maintenance will be applied depending on the organizational technical characteristics. This paper presents an analysis of the specialized literature in the field of maintenance, which allows the identification of further research directions.
2023 ICPR27 66 [9478] Elaboration of a corporate sustainability strategy in an automotive company Pablo Carpejani (Department of Industrial and Systems Engineering, Pontifical Catholic University of Parana), Edson Pinheiro de Lima (Department of Industrial and Systems Engineering, Federal University of Technology), Ubirata Tortato (Department of Industrial and Systems Engineering and Department of Business, Pontifical Catholic University of Parana), Sergio E. Gouvea da Costa (Department of Industrial and Systems Engineering, Federal University of Technology), Fernando Deschamps (Department of Industrial and Systems Engineering, Pontifical Catholic University of Parana) and Marcelo Miguel Tibes Peluso (Department of Industrial and Systems Engineering, Federal University of Technology). Abstract One of the most adopted principles in the automotive sector is continuous improvement, whether in processes, actions, or tasks. Corporate sustainability management in this sector is also influenced by improved performance. There is great competition between different companies to have the best performance. Therefore, this study aims to integrate the material themes of sustainability into the governance structure for the constitution of a business strategy in a company in the automotive sector. The case study technique based on the benchmarking process was chosen for this. As the main result, a roadmap was prepared, showing improvement paths and strategic integration of actions. [9485] Building a More Resilient Supply Chain: Planning Production Allocation and Freight Rail Transportation in the Face of Disruptions Qian Huang (Daiichi Institute of Technology / Hosei University) and Ruixue Li (Hosei University). Abstract This study examines the role of transportation in global supply chain management, focusing on the global railway express as an attractive alternative to sea, road, and air freight due to its cost and lead-time advantages. The research proposes a supply chain plan that simultaneously considers production areas and transportation routes and accounts for freight rate risk, aiming to optimize operations. The proposed model addresses uncertainties in fare structures across different routes and multiple carrier partnerships in international rail corridors. By adopting a strategic approach to route selection, businesses can balance production and transportation costs while managing market fluctuations and volatility. [9493] Bibliometric Analysis of Research for Resilience in Production and Industrial Systems Emre Bilgin Sari (Dokuz Eylul University, Izmir) and Dusan Sormaz (Ohio University). Abstract The concept of "resilience" is generally used in various disciplines to designate the meanings such as endurance, flexibility, adaptability, and recovery from hardship. For production and industry, "resilience" is used to mean that systems can stand up to crises or unexpected adversities and gain new capabilities by adapting to changes. In this study, the bibliometric analysis of the literature on industrial resilience has been carried out by determining the focus of scientific research in previous years regarding the concept of "resilience" for production and industrial systems. For analysis, production and industrial resilience articles from the Scopus database have been examined within the framework of selected criteria and subjected to bibliometric analysis and visualized with the VOSviewer scientific mapping technique. From the analyzes will be made, as an interesting topic, publication trend of studies will be revealed. The most frequently used keyword has been discovered. In addition to this, the countries, institutions, publication services and researchers of published documents on the subject of industrial resilience have been determined and mapped.
2023 ICPR27 67 [9607] Incentivising-sharing-enabled Placement Strategy on a Reusable Transport Item Sharing Platform Min Guo (Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo, China), Hing Kai Chan (Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo, China), Xiang T. R. Kong (College of Economics, Shenzhen University, Shenzhen, China) and Dimple R. Thadani (Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo, China). Abstract The study focuses on the decision pain points of a B2B sharing platform that provides customised reusable transport item (RTI) leasing, sharing, logistics and storage services. The high cost of RTI placement due to different IoT hardware equipped is a significant challenge for the platform. Furthermore, RTI is often left unused in customers' warehouses despite being rented, making incentivising business customers' sharing and optimising the platform's placement decision crucial. The study develops an optimisation decision framework for RTI placement and financial incentives for business customers to encourage sharing behaviour. The study combines an empirical model and optimisation model to measure the willingness to share (WTS) of business customers in different industries under different incentive settings and required RTIs. The multi-objective optimisation model and corresponding solving algorithm are developed to make optimal RTI purchasing and sharing incentive decisions. The study shows that a shared RTI strategy is effective in reducing the platform's order fulfilment costs and maximising customer welfare by generating additional revenue for them. The results also suggest that the platform should make different decisions based on customers' WTS preferences and RTI reusability. The study's insights can be extended to other B2B sharing platform studies, providing more managerial implications for industrial practitioners in terms of resource placement by incentivising sharing decisions. [9618] MODULAR DIGITAL TWIN FOR GENERATING PRODUCT SUSTAINABILITY INFORMATION Andreas Werner (Fraunhofer IAO), Frauke Schuseil (Fraunhofer IAO) and Moritz Hämmerle (Fraunhofer IAO). Abstract Companies receive many customer inquiries as well as regulatory requirements and strive to offer new services to increase sustainability, leading in total to a rising number of product-related requirements. Digital Twins serve as enablers for meeting these requirements, whereas new challenges arise for companies through the introduction of Digital Twins. Digital Twins represent an order-specific configuration and must be structured differently according to requirements and thus as modularly as possible. The determination of required type, amount and linkage of integrated data and partial models is complex. However, this is necessary to use suitable IT systems, to adapt processes and to deploy employees’ capacities, for being able to fulfil the order increasing product sustainability. This paper aims to provide a concept for a Modular Digital Twin for generating Product Sustainability Information to leverage sustainability potentials towards service-oriented business models. [9630] Mapping robotic assembly planning documents: towards production planning automation Ran Shneor (Ben-Gurion University of the Negev) and Sigal Berman (Ben-Gurion University of the Negev). Abstract Automation of production planning for dexterous robotic processes requires the integration of information from multiple production documents. One of the widespread production documents used in industry is the computer-aided design (CAD) model. CAD models detail geometric topologies relevant to the assembly of rigid objects. However, deformable objects which are common in various industrial assemblies are not represented in CAD and their production definitions are detailed in multiple production documents. A prerequisite to automatic planning of robotic assembly suitable for industrial setups is mapping relevant production documents applied to real-world products in different industry sectors. This study aims at identifying production documents with meaningful information for robotic assembly planning of realworld products, A theoretical analysis was conducted to define robotic assembly planning features, followed by a field study in factories to map relevant production documents. A case study with a real-world electrical product is demonstrated. The datasheet, bill of materials, electric scheme, and job guide were pinpointed as meaningful production
2023 ICPR27 68 documents for robotic assembly planning. Combining production documents can identify production part characteristics and facilitates addressing their assembly requirements for automatic robotic assembly planning procedures suitable for industrial environments. [9683] Improvement empty container management in medium-sized port logistics chains Cecilia Montt (Universidad de Santiago de Chile), Felisa Cordava (Universidad San Sebastian,Chile) and Alejandra Valencia (Ponficia Universidad Catolica de Valparaiso, Chile). Abstract This paper analyses the logistics of empty containers in order to reduce demurrage costs and thus avoid the loss of customer confidence. These are caused by defects in the planning of the logistics chain, which includes the processes from the time the ship arrives with the container at the Port, and by means of land transport, it is taken to an extra-port area to deconsolidate the cargo. The aim of this work is to redesign the empty container process to allow savings in demurrage and better customer service. To do this, first the current situation is diagnosed to determine the causes of demurrage, which is the delay in the delivery of empty containers to the customer, where possible improvements to the process are defined, establishing a plan for their implementation. The diagnosis identifies the bottlenecks and critical processes associated with reception, deconsolidation and transport. A SWOT analysis is carried out for the diagnosis and flow diagrams and Business Process Management (BPM) are applied to redesign the processes to achieve an improvement in the logistics chain, mainly its planning and coordination. To this end, a set of indicators is developed to evaluate the redesign processes. Finally, a change management proposal is presented. As a result, delays in the delivery of empty containers are expected to be reduced from 5.6% to 2%. [9685] Assessment Framework for Advanced Systems Engineering Benjamin Schneider (Fraunhofer Institute for Industrial Engineering IAO), Stephan Schüle (Fraunhofer Institute for Industrial Engineering IAO), Mehmet Kürümlüoglu (Fraunhofer Institute for Industrial Engineering IAO) and Oliver Riedel (Fraunhofer Institute for Industrial Engineering IAO). Abstract Advanced Systems Engineering (ASE) is a new paradigm for the engineering of todays and future market offerings such as systems of systems or product service systems. Companies currently face challenges in engineering regarding complexity of systems, need for interdisciplinary collaboration and steadily increasing demands form market and regulatory side. The ASE paradigm promotes the application of ASE technologies such as model-based systems engineering, data continuity, software-defined-x, artificial intelligence and collaborative visualization. To ensure a seamless integration (digital thread) as well as a structured transformation, these have to be selected and implemented in a company-specific manner considering the current strategy, organization, methods and tool, employee skills and processes of the company. This paper presents an assessment framework for company-specific evaluation with regard to the ASE paradigm, which aims at providing tailored implementation plans for ASE solutions. The relevant dimensions and building blocks as well as the assessment method will be presented and described. Learnings from the application of the assessment framework gained from several case studies conducted with small and medium-sized enterprises (SMEs) will be presented and discussed. [9695] GAF-Based Time Series Imaging Transformation Applying Angle of Intersections Matrix for Time Series Classification Yonggon Jung (Korea University, Industrial and Management Engineering) and Jun-Geol Baek (Korea University, Industrial and Management Engineering). Abstract In the manufacturing process, continuous efforts are made to improve production quality by building machine learningbased classification models to identify machine wear or product defects from time-series data. Previous studies used 1NN-DTW to measure and cluster the similarity between two time series, or to transform the time series into a twodimensional image through Fourier or Wavelet transform and apply it to a deep learning model for classification.
2023 ICPR27 69 However, there are some disadvantages in that the temporal information disappears, and the performance fluctuates significantly depending on the basis function or basis wavelet region. In this paper, we propose an Angle of Intersections Matrix that improves classification performance by adding the proposed matrix to the Gramian Angular Fields (GAF) method in a way that can extract additional information from time series data. The proposed method shows improved classification performance compared to original GAF-based methods in identifying and classifying wear and defects. [9747] Comparison of Competence Sources in Technology-Intensive Work Systems in Public Transport Maintenance Markus Steinlechner (Fraunhofer Austria Research GmbH), Marlies Negele (Fraunhofer Austria Research GmbH), Rafael Vrecar (TU Wien), Aaron Wedral (TU Wien), Astrid Weiss (TU Wien) and Sebastian Schlund (TU Wien). Abstract In the current competitive market, manufacturing enterprises face significant shortage of skilled workers and an increasingly aging workforce. Thus, workers with different educational backgrounds, skills, experience, and, in fact, age and cultural backgrounds must be integrated into existing work structures. This challenge is amplified considering the increasing complexity of working environments. This paper extends the state-of-the-art in the research field of “Competence Management” by examining and evaluating target competence sources in technology-rich work environments. Target competence sources have a significant influence on defined target competencies and therefore need to be examined before defining target competencies. If target competence sources are not sufficiently studied and compared, the wrong competencies may be defined. The main objective of this paper is the numerical evaluation of different target competence sources using a combination of quantitative and qualitative methods. The target competence sources have been selected based on a prototypical work system for public transportation maintenance. Evaluations are conducted by experts from public transport operators. [9887] Improving the quality of rapid prototyping processes of electronic control units by using a dedicated software platform Adrian Bogorin Predescu (Politehnica University of Bucharest), Aurel Mihail Titu (Lucian Blaga University of Sibiu) and Constantin Oprean (Lucian Blaga University of Sibiu). Abstract The scientific paper presents the possibilities of improving the quality of the rapid prototyping processes of the electronic control units using a dedicated software platform. Embedded systems (ECU – Electronic Control Unit) products are analyzed, based on an original communication protocol through which the state of the system can be diagnosed in real time in different phases of development. This software platform called BIOComProP (Basic Input Output Communication Platform) is used especially in the ECU prototype phase for the individual testing of each hardware component connected to the inputs and outputs of the microcontroller which is the command and control element of the ECU . The BIOComProP platform is intended to be portable and extensible on any microcontroller family from different suppliers of electronic components and brings added value to reduce the development and implementation time of new projects based on this platform. The platform consists of two parts: BIOComProP_ECU - the software that runs in the ECU and BIOComProP_TS - the software that runs on the computer where ECU diagnostics and testing are performed. The authors also present a dedicated research methodology as well as the research results and not least the conclusions obtained. [9927] Enhancing Machinery Performance and Minimizing Downtime with Real-Time Analytics and Machine Monitoring Emilia Brad (Technical University of Cluj-Napoca), Miruna Peris (Technical University of Cluj-Napoca), Ionut Chis (Technical University of Cluj-Napoca) and Vlad Trifan (Technical University of Cluj-Napoca). Abstract This paper introduces a real-time analytics and machine monitoring system, underpinned by a methodologically rigorous approach, aimed at minimizing machinery downtime and enhancing performance. The system grants immediate access
2023 ICPR27 70 to machine status, allowing for rapid scheduling of repairs and replacements, thereby reducing company downtime. Our solution utilizes Visual Studio and the C-Sharp programming language to extract data from Fanuc CNC machine-tools. This data is stored in a SQLite database and can be exported as a CSV file. FastAPI, a widely-used Python web framework, is employed to generate real-time charts for being analysed by operators. The research methodology combines experimental and observational methods, applied to a Fanuc CNC machine-tool, to assess servo motor loads. The experimental design comprises controlled alterations in machine operating conditions, evaluating their impact on performance. Simultaneously, the observational aspect involves real-time data monitoring to discern patterns and anomalies. The findings reveal that the system effectively streamlines part production time, resulting in shorter manufacturing duration, reduced costs, and increased overall efficiency. Through the timely provision of machine status information, the system facilitates prompt scheduling of repairs and replacements, leading to cost reduction and improved productivity. [9995] Three-stage data-driven approach to fast and accurate job dispatching using learning-torank techniques Young-Suk Han (Kyung Hee University) and Jae-Yoon Jung (Kyung Hee University). Abstract Recently, a few studies have been conducted to construct data-driven job dispatching methods for hybrid flow shop such as semiconductor and display manufacturing systems. The data-driven job dispatching models can be used to simulate the production scheduling or dispatching without knowing the original dispatching rules. To learn historical job dispatching data, they adopt machine learning and deep learning methods for classification, which specifically aim at choosing the dispatched job among candidate jobs. However, such classification-based job dispatching engines often take a long inference time despite high accuracy because they require a lot of comparison between among jobs. This paper proposes a three-stage modeling approach that filters prioritized jobs using a machine-learned ranking technique before performing a pairwise comparison. The method was evaluated using two major semiconductor process datasets obtained from a commercial simulation-based scheduling engine. The experimental results demonstrate that the proposed method outperforms the traditional pairwise dispatching model in terms of speed while maintaining high dispatching accuracy.
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