INDUSTRY 4.0 - TERMS, CONCEPTS AND METAPHORS

INDUSTRY 4.0

TERMS, CONCEPTS
AND METAPHORS

PART 1: CLOUD COMPUTING

HISTORY

Everyone is talking about it, but what do we actually mean by Cloud and
Cloud Computing? In fact, the Cloud metaphor is rather old. It was first
used in the discussions around ARPANET (1977) and CSNET (1981), both
predecessors of today’s Internet. Back then, the term ‘Cloud’ already
described a vision where computing power and data were flexibly
accessible – independent from physical devices and location.

What was a futuristic vision in the 1980’s and 1990’s entered into practical
solution concepts in the 2000’s, hand-in-hand with exciting progress
in computation power, storage technology, Internet bandwidth and
mobile wireless communication technology. Various NASA- and European
Commission-funded projects provided the basic technical and legal
foundation. Already by mid-2008, the leading technology research
company Gartner1 saw that “organisations are switching from company-
owned hardware and software assets (CAPEX) to pay-per-use service-based
models (OPEX)”. This commercial outlook was also the starting-point for big
commercial players like Amazon, Microsoft, IBM, Google, SAP, Oracle, Cisco
and others to enter into very substantial investments for providing the
required Cloud infrastructure. Today, Cloud Computing is a rather mature
technology that has evolved by thoroughly addressing the QoS (quality of
service) and reliability problems of the past.

Currently, Cloud Computing is one of the fastest growing business models.
Based on concepts like virtualizations, on-demand-resources, Service-
oriented-Architectures (SoA) and pay-per-use, many companies start to
re-evaluate their fundamental IT strategy. Throughout the community of
small-, mid-sized- and large enterprises, discussions about Infrastructure as
a Service (IaaS), Platform as a Service (PaaS) and Software or Application

1 https://www.gartner.com/newsroom/id/742913

as a Service (SaaS) are arising. The fourth industrial revolution and the
resulting Industrial Internet of Things (IIoT) are adding new requirements
due to merging the former separate worlds of IT and OT (Operations
Technologies in our factories). This merger calls for enhancing the original
cloud concept by smart technologies for decentralisation and pre-
processing, commonly called Edge, Fog, Mist and Dew computing.

PART 2: IAAS, PAAS, SAAS

CLOUD SERVICES

After examining the history of Cloud Computing in Part 1 of our
terminology-series, part 2 will translate the three very fundamental Cloud
Computing Services – IaaS, PaaS and SaaS. Besides looking at the concept
basics, we will outline the potential benefits of these Cloud Services for the
future of industrial manufacturing.

Cloud computing often indicates its potential to provide ‘Everything as a
Service’ (EaaS). Nevertheless, the US National Institute of Standards and
Technology describes three basic service levels: IaaS, PaaS and SaaS.

IAAS: INFRASTRUCTURE AS A SERVICE

Until recently, most companies operated their own local data centers. This
required substantial investment in servers, storage media, firewalls and related
infrastructure such as standby power supplies. But operating a secure ISO
27001 certified Data Center stands for very substantial capital expenditures
(CAPEX) as well as operating expenditures (OPEX) for the required energy and
personnel. Cloud Computing offers an attractive alternative, allowing to switch
from company-owned assets to service-based operating models (pure OPEX).
Infrastructure as a Service (IaaS) includes all fundamental computing resources
and the maintenance thereof operated by a cloud provider. Companies are
then able to deploy and run their software, which includes operating systems,
engineering tools, technology libraries and applications onto such cloud
infrastructure. One great advantage of IaaS is that a manufacturing company
gets access to a fully scalable computing performance. Whenever needed,
performance can easily (and automatically) be up- and downgraded.

PAAS: PLATFORM AS A SERVICE

Platform as a Service (PaaS) goes one step beyond Infrastructure as a Service
(IaaS). While IaaS is mainly addressing IT administrators, PaaS is in the
hands of software application developers. With PaaS, the cloud provider’s
responsibility and service does not end with providing and maintaining the
basic computing infrastructure. Platform as a Service stands for a model,
where companies are also freed from purchasing and maintaining operating
systems, software engineering tools, technology libraries and databases.
Typical examples for PaaS offers are Microsoft Azure and Google App Engine.
Platform as a Service allows saving even more CAPEX and local maintenance
efforts. Based on the PaaS model, companies can therefore fully focus
on creating and deploying their own software applications (or acquired
applications) onto such a cloud platform – no more worries about databases,
tools, libraries and operating systems. Still, the company has full control and
responsibility over the deployed applications and configuration settings.
They still ‘own’ their application software.

SAAS: SOFTWARE AS A SERVICE

With Software as a Service (SaaS), the cloud provider provides and
maintains the complete package, infrastructure, platform and the
application software as well as databases on his cloud infrastructure.
The applications are then accessible from various client devices through
either a web browser or a specific program interface. Examples for this
are Office 365 from Microsoft or cloud based ERP solutions. Software as a
Service interacts directly with the actual users of application software and
is sometimes referred to as ‘on-demand software’ and is usually priced on a
pay-per-use basis or using a subscription fee.

FUTURE OUTLOOK

Looking at the complete package with Software as a Service (SaaS),
businesses are able to reallocate IT operations costs away from hardware/
software spending and personnel expenses towards meeting their primary

business goals. One drawback of SaaS still comes with storing the users’
data on the cloud provider’s server. As a result, there could be unauthorised
access to the data. For this reason, users are increasingly adopting
intelligent third party key management systems to help secure their
data. Other ways to overcome the security and privacy obstacles are by
operating ‘Private Cloud’ or ‘Hybrid Cloud’ solutions where the entire cloud
infrastructure is either completely operated inside a company or is shared
between an internal cloud and Public or Community Cloud solutions.

CLOUD COMPUTING: ONE OF THE MOST DYNAMICALLY GROWING
BUSINESS SEGMENTS
Cloud computing is still as much a research topic as it is a market offering.
The major cloud technology developers continue to invest billions a year in
cloud R&D; for example: in 2011 Microsoft committed 90% of its US$9.6bn
R&D budget to its cloud1. In a press release, Gartner states that they expect
the worldwide SaaS market to grow to $75bn in 2020. Additionally, more
industries are turning to cloud technology as an efficient way to improve
quality services due to its capabilities to reduce overhead costs, downtime,
and automate infrastructure deployment.

1 Bloomberg (2011)

PART 3: FOG / EDGE
COMPUTING

LIFTING THE FOG

After examining the history of Cloud Computing in part 1 and explaining the
three fundamental Cloud Computing services in part 2 we will now focus on
two of the latest buzz-words created by the IoT and IIoT community (IIoT =
Industrial Internet of Things): Fog and Edge Computing.

ON THE EDGE

According to CISCO, Fog Computing is a term that refers to extending
Cloud Computing to the edge of an enterprise’s network. Therefore, Fog
Computing is often also referred to as Edge Computing or fogging. In that
sense, Fog Computing is a logical consequence of the rapidly growing
utilisation of the Cloud. Fog Computing simply facilitates the operation
between end-devices (such as IIoT capable machines, equipment,
augmented reality devices, wearables etc.) and the Cloud Computing
data centers by supporting mainly computation, storage and networking
services.

EMERGING USE-CASES

Following the above provided definition, Fog Computing is a decentralised
computing infrastructure in which computing resources and application
services are distributed in the most logical, efficient place at any point from
the data source to the cloud. In the reality of brownfield (existing factories),
Fog or Edge solutions offer very powerful new possibilities. Smart new
systems like APROL from B&R can help to achieve quick wins by providing
services such as:

- Flexible and high-speed process data acquisition from all the existing (old)
machines and equipment as well as for the latest (smart) investments

- Providing powerful Condition Monitoring and Energy Management
preprocessing
- Providing virtualisation features and central data management for all linked
sub systems (softwares, firmwares, configurations)
- Converting heterogeneous data into standardised and secure formats
- Compressing and storing huge amounts of data into relevant information
before forwarding to the Cloud
- Providing algorithms for autonomous local decision making in the range of
milliseconds
- Providing local algorithms for visualising e.g. performance, quality and
availability KPIs such as OEE – Overall Equipment Effectiveness.

FUTURE OUTLOOK: CENTRAL MANAGEMENT OF
DECENTRALISED SOLUTIONS

Early Cloud Computing enthusiasts were predicting that our future Smart
Factories will be completely run from remote Cloud Computing Data
Centers – and that is probably true when we look at the data management
(central management of all softwares, firmwares and configurations of all
intelligent items in a factory).

For our highly flexible and highly available production needs, Fog
Computing will become an essential part of the future architectures. This is
of great importance, since we will see a lot of small, distributed intelligence
on our future mechatronic modules and machines, which is dealing with
controlling sensors and actuators and safety equipment in milliseconds
and microseconds speed. In that sense, Fog Computing will take care
of providing the required central data management and pre-processing
infrastructure for the powerful decentralised solutions of the future.

Another interesting aspect of Fog Computing will be in the acquisition
and orchestration of all the data gathered in a factory. We will see growing
demands of segmenting such data in a way that data-ownership is under
control and respected.

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