ArticlePDF Available

Abstract and Figures

The term "Industry 4.0" was initially coined by the German government which describes and encapsulates a set of technological changes in manufacturing and sets out priorities of a coherent policy framework with the purpose of maintaining the global competitiveness of German industry. Industry 4.0 has brought many professions to change. People are obligated to learn new, everyday tasks but now are also compelled to use hi-tech gadgets which are fast becoming the most important factor in their working life. In this paper, the general definition of Industry 4.0 will be discussed. Generally, Industry 4.0 refers to the means of automation and data exchange in manufacturing technologies including Cyber-Physical Systems, Internet of Things, big data and analytics, augmented reality, additive manufacturing, simulation, horizontal and vertical system integration, autonomous robots as well as cloud computing. It serves a role to help integrate and combine the intelligent machines, human actors, physical objects, manufacturing lines and processes across organizational stages to build new types of technical data, systematic and high agility value chains. All these components will also be discussed in this paper. Additionally, government initiatives by various countries toward Industry 4.0 will also be presented in this paper.
Content may be subject to copyright.
Jour of Adv Research in Dynamical & Control Systems, Vol. 10, 14-Special Issue, 2018
ISSN 1943-023X
Received: 20 October 2018/Accepted: 15 November 2018
1379
An Overview of Industry 4.0: Definition,
Components, and Government Initiatives
S.I. Tay, Department of Production and Operation Management, Faculty of Technology Management and Business, Universiti
Tun Hussein Onn Malaysia (UTHM), Parit Raja, Batu Pahat, Johor, Malaysia. E-mail: hp170077@siswa.uthm.edu.my
T.C. Lee*, Department of Production and Operation Management, Faculty of Technology Management and Business, Universiti
Tun Hussein Onn Malaysia (UTHM), Parit Raja, Batu Pahat, Johor, Malaysia. E-mail: tclee@uthm.edu.my
N.A. A. Hamid, Department of Production and Operation Management, Faculty of Technology Management and Business,
Universiti Tun Hussein Onn Malaysia (UTHM), Parit Raja, Batu Pahat, Johor, Malaysia. E-mail: aziati@uthm.edu.my
A.N.A. Ahmad, Department of Production and Operation Management, Faculty of Technology Management and Business,
Universiti Tun Hussein Onn Malaysia (UTHM), Parit Raja, Batu Pahat, Johor, Malaysia. E-mail: aizat@uthm.edu.my
Abstract--- The term “Industry 4.0” was initially coined by the German government which describes and
encapsulates a set of technological changes in manufacturing and sets out priorities of a coherent policy framework
with the purpose of maintaining the global competitiveness of German industry. Industry 4.0 has brought many
professions to change. People are obligated to learn new, everyday tasks but now are also compelled to use hi-tech
gadgets which are fast becoming the most important factor in their working life. In this paper, the general definition
of Industry 4.0 will be discussed. Generally, Industry 4.0 refers to the means of automation and data exchange in
manufacturing technologies including Cyber-Physical Systems, Internet of Things, big data and analytics,
augmented reality, additive manufacturing, simulation, horizontal and vertical system integration, autonomous
robots as well as cloud computing. It serves a role to help integrate and combine the intelligent machines, human
actors, physical objects, manufacturing lines and processes across organizational stages to build new types of
technical data, systematic and high agility value chains. All these components will also be discussed in this paper.
Additionally, government initiatives by various countries toward Industry 4.0 will also be presented in this paper.
I.
Introduction Industry 4.0
Before Industry 4.0, there were three prior industrial revolutions that have led to changes of paradigm in the
domain of manufacturing: mechanization through water and steam power, mass production in assembly lines and
automation using information technology.
Industry 1.0 began around the 1780s with the introduction of water and steam power which helped in mechanical
production and improved the agriculture sector greatly. Next, Industry 2.0 is defined as the period when mass
production was introduced as the primary means to production, in general. The mass production of steel helped
introduce railways into the industrial system which consequently contributed to mass production at large.
During the 20th century, Industry 3.0 arose with the advent of the Digital Revolution which is more familiar
compared to Industry 1.0 and 2.0 as most people living today are familiar with industries leaning on digital
technologies in production. Perhaps Industry 3.0 was and still is a direct result of the huge development in
computers and information and communication technology industries for many countries (Liao et al., 2017).Industry
4.0 has brought change to many professions. People have always been obligated to learn new everyday tasks but
now are also compelled to use hi-tech gadgets which are fast becoming the most important factor in their working
life (Gorecky et al., 2014).
Industry 4.0 is being presented as an overall change by digitalization and automation of every part of the
company, as well as the manufacturing process. Big international companies that use concepts of continuous
improvement and have high standards for research and development will accept the concept of Industry 4.0 and
make themselves even more competitive in the market (Marcos et al., 2017).
This becomes possible by introducing self-optimization, self-cognition, and self-customization into the industry.
The manufacturers will be able to communicate with computers rather than operate them. The schematic diagram of
overview for the industrial revolutions is illustrated in Figure 1.
Jour of Adv Research in Dynamical & Control Systems, Vol. 10, 14-Special Issue, 2018
ISSN 1943-023X
Received: 20 October 2018/Accepted: 15 November 2018
1389
II.
Definition of Industry 4.0
Figure 1: The Industrial Revolution
Industry 4.0 enables the manufacturing sector to become digitalized with built-in sensing devices virtually in all
manufacturing components, products and equipment. The analyzing of related data within a ubiquitous system with
the fusion of digital data and physical objects has the ability to transform every industrial sector in the world to
evolve much faster and with greater impact than any of the three previous industrial revolutions i.e. Industry 1.0,2.0
and 3.0(Mrugalka & Wyrwicka, 2017). Hence, Industry 4.0 is a contemporary issue that concerns today’s industrial
production as a whole and is meant to revolutionize it. In 2011, Germany introduced Industry 4.0 at the Hannover
Fair event, symbolizing the advent of a brand new era of industrial revolution. When the idea was first mooted,
extensive efforts were undertaken by the European manufacturing researchers and companies to embrace it. Their
interest in this project or concept is due to the fact that under Industry 4.0, production will become more efficient
and less costly. This is achieved by easy exchange of information and the integrated control of manufacturing
products and machines acting simultaneously and smartly in interoperability (Qin, Liu &Grosvenor, 2016). However,
different researchers have different perceptions on the true meaning of Industry 4.0. Table 1 shows the different
definitions of Industry 4.0 by different authors.
Jour of Adv Research in Dynamical & Control Systems, Vol. 10, 14-Special Issue, 2018
ISSN 1943-023X
Received: 20 October 2018/Accepted: 15 November 2018
1381
Table 1: Summary of Definition of Industry 4.0
most of the authors outlined the meaning of Industry 4.0 to consist of key topics
related to Cyber-Physical Systems (CPS), Internet of Things (IoT), industrial Internet and others. Besides that, some
of the authors concentrated Industry 4.0 on the cost factor and profitability with recently developed high-tech
information and intelligent services. From previous research on Industry 4.0,in the beginning the focus was mostly
on the sector of industrial manufacturing but currently many sectors such as automotive, engineering, chemical, and
electronics are beginning to implement Industry 4.0.In summary, Industry 4.0 is aggregating existing ideas into a
new value chain which plays a crucial role to transform whole value chains of life cycles of goods while developing
innovative products in manufacturing which involves the connection of systems and things that create self-
organizing and dynamic control within the organization. Industry 4.0 describes a future scenario of industrial
production that is characterized by new levels of controlling, organizing and transforming the entire value chain with
the life cycle of products,resulting in higher productivity and flexibility through three types of effective integration
which are horizontal, vertical and end-to-end engineering integration. Hence, these can predict product performance
degradation and autonomously manage and optimize product service needs and consumption of resources, then lead
to optimization and reduction of costs. Next, aspects of the creation of dynamic, real-time optimized and self-
organizing cross-company value networks through the Cyber-Physical Systems (CPS), Internet of Things (IoT),
artificial intelligence, additive manufacturing, cloud computing and others are added. All these components are
requirements and are parts of the visionary concept of Industry 4.0.
Author and
year
Definition
Kagermann ,
Wahlster &
Johannes.
(2013)
Industry 4.0 utilizing the power of communications technology and innovative inventions to
boost the development of the manufacturing industry.
Qin, Liu &
Grosvenor
(2016)
Industry 4.0 encourages manufacturing efficiency by collecting data smartly, making correct
decisions and executing decisions without any doubts. By using the most advanced
technologies, the procedures of collecting and interpreting data will be easier. The
interoperability operating ability acts as a ‘connecting bridge’ to provide a reliable
manufacturing environment in Industry 4.0. This overall consciousness gives Industry 4.0 the
most important aspect of artificial intelligent functions.
Schumacher,
Erol & Sihn,
(2016)
Industry 4.0 is surrounded by a huge network of advanced technologies across the value-chain.
Service, Automation, Artificial Intelligence Robotics, Internet of Things and Additive
Manufacturing are bringing in a brand new era of manufacturing processes. The boundaries
between the real world and virtual reality is getting blurrier and causing a phenomenon known
as Cyber-Physical Production Systems (CPPS).
Schwab
(2016)
Industry 4.0 is differentiated by a few characteristics of new technologies, for example:
physical, digital, and biological worlds. The improvement in technologies is bringing significant
effects on industries, economies and governments’ development plans. Schwab pointed out that
Industry 4.0 is one of the most important concept in the development of global industry and the
world economy.
Wang et al.,
(2016)
Industry 4.0 makes full use of emerging technologies and rapid development of machines and
tools to cope with global challenges in order to improve industry levels. The main concept of
Industry 4.0 is to utilize the advanced information technology to deploy IoT services.
Production can run faster and smoothly with minimum downtime by integrating engineering
knowledge. Therefore, the product built will be of better quality, production systems are more
efficient, easier to maintain and achieve cost savings.
Mrugalska &
Magdalena
(2017)
The modern and more sophisticated machines and tools with advanced software and networked
sensors can be used to plan, predict, adjust and control the societal outcome and business
models to create another phase of value chain organization and it can be managed throughout
the whole cycle of a product. Thus, Industry 4.0 is an advantage to stay competitive in any
industry. To create a more dynamic flow of production, optimization of value chain has to be
autonomously controlled.
According to the table above,
Jour of Adv Research in Dynamical & Control Systems, Vol. 10, 14-Special Issue, 2018
ISSN 1943-023X
Received: 20 October 2018/Accepted: 15 November 2018
1382
III.
Components of Industry 4.0
Industry 4.0 can be classified into three components. The first is horizontal integration. It brings the concept of a
new type of worldwide value chain networks. The second is vertical integration. The concept is to achieve
hierarchical subsystems at the production line to produce an easy to configure and high flexibility production line.
The last component is engineering integration along the whole value chain from the beginning to the end to assist in
the customization of products. The horizontal integration is described as one where a corporation should both
cooperate and compete with corporations that have similar characteristics to create an efficient production system.
Material, financial control and knowledge can be connected in all these companies easily. Therefore, new control
systems and models for business may appear (Wang et al., 2016). Vertical integration delivers the idea of a factory
that has various informational and physical subsystems, for example like production management, actuator and
sensor, value and corporate planning. It is important for the vertical integration of sensor and actuator signals along
various stages of the enterprise resource planning (ERP) level to ensure high flexibility and ease to configure
production lines. From this integration, the highly intelligent machines create an automated controlled system that is
able to be automatically reconfigured according to the various types of products. The large amounts of data collected
and processed enables the manufacturing system to be transparent(Wang et al., 2016). Lastly, End-To-End
engineering integration in a chain of activities throughout the product-centric value creation process involves aspects
such as customer requirement expression, product development and design, recycling, production engineering,
production services, production planning and maintenance. From end-to-end integration, every stage can be reused
for the same product model. Product design effects on services and production can be predicted by utilizing a
software tool in the chain to make sure the products are customizable (Wang et al., 2016).
IV.
Characteristics of Industry 4.0
Industry 4.0 is the future of global manufacturing. It is the era of automation, of the digitalized factory and
digitalized products the fourth phase of industrial revolution, or Industry 4.0. Nevertheless, the academics field is
still unable to define the approach as the Industry 4.0 is the basic term referring to the fourth industrial revolution.
This causes difficulty to distinguish its components. There are 9 characteristics for industry as shown in Figure 2
below.
Figure 2: Characteristics of Industry 4.0.
Jour of Adv Research in Dynamical & Control Systems, Vol. 10, 14-Special Issue, 2018
ISSN 1943-023X
Received: 20 October 2018/Accepted: 15 November 2018
1383
Cyber-Physical System (CPS)
Industry 4.0 can be played as a Cyber-Physical System study where the advances and speed of development in
communication and calculation form the Cyber-Physical System and Industry 4.0. Each production system of CPS
has sensors installed in the entire physical aspects in order to connect the physical things with virtual models. Due to
Cyber-Physical System to be more common in society and occurs during interaction with humans, it must be
ensured that CPS behave stably and has a certain bearing when utilized with artificial intelligence (AI) (Mosterman
& Zender, 2015).CPS is also the foundation to create the Internet of Things (IoT) which can be combined to become
the Internet of Services (IoS).Hence, businesses will find it easier to establish global networks which joins the
warehousing systems, machinery and production facilities of CPS in the future(He, 2016).
Internet of Things (IoT)
Industry 4.0 is the new phrase for the combination of the present Internet of Things (IoT) technology and the
manufacturing industry. Industry 4.0 was initiated as a result of the combination of the Internet of Things (IoT) and
the Internet of Services (IoS) in the manufacturing process (Kagermann, Wahlster & Johannes (2013). Generally,
IoT can provide advanced connectivity of systems, services, physical objects, enables object-to-object
communication and data sharing. IoT can be achieved through the control and automation of aspects like heating,
lighting, machining and remote monitoring in various industries (Zhong et al., 2017).
Internet of Services (IoS)
Internet of Services acts as important components in the automotive industry. Activities are triggered through
data transfers in the information technology to make daily mobility safer, easier and pleasant. The Internet of
Services (IoS) acts as “service vendors” to provide services through the internet according to the types of
digitalization services. These services are available and on demand around business models, partners and any setup
for services. The suppliers provide and aggregate the services into additional value services as communication
among consumers can be received and accessed by them through various channels( Buxmann, Hess, & Ruggaber,
2009).
Big Data and Analytics
Under Industry 4.0, big data analytics is beneficial for predictive manufacturing and is an important direction for
industrial technology development through the rapid development of the Internet. This leads to huge amounts of
information produced and obtained daily where current processing and analysis is unable to cope using traditional
methods. Hence, big data has become a hot topic recently in Industry 4.0. Many other applications would be able to
gain additional values when existing techniques become more mature to handle big data. Big data is the utilization
of digital technology to conduct analysis. According to Forrester’s definition, “Big Data” can be divided into four
dimensions which are volume, variety, value and velocity(Witkowski, 2017).
Augmented Reality
Augmented Reality (AR) has begun to be considered as one of the most promising business that technological
companies should heavily invest in. This technology can bring huge support for maintenance works in business due
to reduced time needed for maintenance works and reduction of potential errors in maintenance works. It can predict
with high accuracy and allows the frequency of maintenance to be kept at low numbers by utilizing predictive
maintenance to prevent any unplanned reactive maintenance. This will reduce costs associated with doing too much
preventive maintenance(Masoni et al., 2017).
Autonomous Robots
Current robots have higher flexibility, advanced functions and are easier to operate in multitudes of fields. In the
near future, robots will interact with each other and collaborate actively with humans under the guidance of handlers.
These robots will be cheaper and more sophisticated in order to achieve better abilities compared to those currently
used in the manufacturing field.
Additive Manufacturing (3D Printing)
Industry 4.0 is stimulating the utilization of advanced data technologies and smart production systems. Hence,
additive manufacturing is one of the crucial tools to embrace Industry 4.0. The implementation of new
manufacturing skills for the purpose of integrating information technologies plays a crucial role in the
competitiveness of the economy. The advancement of cyber technology has encouraged the transition to Industry 4.0.
The trend of looking for new materials available using additive manufacturing is increasing. Certain required
Jour of Adv Research in Dynamical & Control Systems, Vol. 10, 14-Special Issue, 2018
ISSN 1943-023X
Received: 20 October 2018/Accepted: 15 November 2018
1384
characteristics of a material can be achieved by metallic constituents and smart materials. In fact, the implementation
of Industry 4.0 hugely depends on the capabilities of additive manufacturing (Dilberoglu et al,. 2017).
h) Cloud Computing (CM)
Cloud computing is a relatively new system logic that provides a huge space of storage for the user. A small
amount of money allows enterprises or individuals to access these resources. Over time, the performance of
technologies keep on improving, however, the functionality of machine data will continue to be stored into the cloud
storage system, allowing production systems to be more data-driven. Company limitations can be minimized since
more data sharing will occur across sites for production-related undertakings in the industrial revolution. Cloud
computing is slowly becoming a consideration by many companies during their data systems build. Even if software
was traditionally not kept in clouds, the amount of applications being developed in clouds is gradually increasing
(Xu, 2012).
Simulation
Simulation modelling is a way of running a real or virtual process or a system to find out or guess the output of
the modelled system or process. Simulations are done by using real-time data to represent the real world in a
simulation model, which include humans, products and machines. Therefore, operators are able to optimize the
machine settings in a virtual simulated situation before implementing in the physical world. This decreases machine
setup times and improves quality. Latest revolutions in the simulation modelling paradigm enable modelling of
manufacturing systems and other systems through the virtual factory concept. Furthermore, advanced artificial
intelligence (cognitive) on process control, including autonomous adjustments to the operation systems (self-
organization) can also be done through simulations (Rodič, 2017).
V.
Government Initiatives
Industry 4.0 is defined as an amalgamation of advanced technologies where the internet is extensively used to
support certain technologies such as embedded systems. It serves a role to integrate and combine the intelligent
machines, human actors, physical objects, manufacturing lines and processes across organizational stages, building
new types of technical data, systematic systems and high agility value chains (Schumacher, Erol & Sihn,
2016).Germany launched the strategic initiative mooted in 2011 under its High-Tech Strategy 2020 with the purpose
to switch from centralized to decentralized networks which connect devices and equipments that communicate with
each other and able to respond accordingly to gain information for revolutionizing the manufacturing industry(Wang
et al., 2016). Kagermann, Wahlster & Johannes in 2013 had published the main ideas of the fourth industrial
revolution to construct the base for the Industry 4.0 manifesto. The study was published by the German National
Academy of Science and Engineering in 2013. The Public Private Partnership (PPP) for Factories of the Future (FoF)
deployed and initiated discussions on related topics of Industry 4.0 at the European level. In the United States of
America, the Industrial Internet Consortium (ICC)promoted Industry 4.0 (Liao et al., 2017). This new industrial
revolution provides scope for many of the basic ideas that had been widely implemented in many other countries.
Internationally, many governments have realized the trend and have taken action to react specifically to the impact
Industry 4.0 would bring to the manufacturing industry. Some of the governments’ plans are as stated below:
(a) In 2011, to make sure the United States of America (USA) will be well prepared for the next generation of
manufacturing revolution, USA President Barack Obama started a series of national-level actions, discussions and
recommendations, titled Advanced Manufacturing Partnership (AMP)’, (President’s Council of Advisors on
Science and Technology, 2014). AMP was an initiative undertaken to make more USA companies ready to invest
heavily in advanced technology. In 2017, the global programmable logic controller market was estimated at USD
8.491 billion and is expected to achieve USD 10.595 billion by 2023, registering a CAGR of 3.7% during 2018-
2023 (the forecast period).
(b) In 2012, an action plan known as High-Tech Strategy 2020’ was passed by the German government. This
project grants billions of Euros each year to develop the latest technologies in the manufacturing industry (Liao et al.,
2017). In 2018, Volkswagen introduced the 48V progressive hybrid, VTG turbocharger and Miller combustion
process and mild hybrid diesel systems for its new vehicles.
(c) In 2013, the French government launched ‘La Nouvelle France Industrielle’. This program prioritized 34
sector-based ways in France’s industrial policy (Conseil national de l’industrie 2013). French start -up 2B1st
Consulting introduced at Hannover Messe a collaborative digital tool designed to help companies implement
Industry 4.0 solutions.
Jour of Adv Research in Dynamical & Control Systems, Vol. 10, 14-Special Issue, 2018
ISSN 1943-023X
Received: 20 October 2018/Accepted: 15 November 2018
1385
(d) In 2013, a long term action plan for the manufacturing industry in the United Kingdom (UK) called the
‘Future of Manufacturing’ was implemented. This program refocused and rebalanced the policies to support the
resilience of UK manufacturing until 2050(Foresight, 2013). In 2018, Rolls-Royce is partnering with the Alan
Turing Institute to explore how Artificial Intelligence (AI) and analytics can be applied at scale to supply chains and
predictive maintenance regimes.
(e) In ‘Factories of the Future (FoF)’in 2014, the European Commission adopted a new contractual Public-
Private Partnership (PPP). A total of almost 80 billion Euros of funding for the consecutive 7 years in the period of
2014 to 2020 will be provided for the program Horizon 2020(European Factories of the Future Research Association,
2016). In 2018, the European Commission announced a new series of measures to put artificial intelligence (AI) at
the service of citizens and boost Europe’s competitiveness in the field with a budget of €20 billion by the end of
2020.
(f) ‘Innovation in Manufacturing 3.0’, a plan launched by the South Koreans in 2014 had emphasized four ways
and tasks for improvement of Korean manufacturing (Ministry of Trade Industry and Energy of South Korea, 2014).
As a result, Hyundai developed a new autonomous car, the Hyundai Genesis sedan, which is capable of tracking
moving objects, avoiding collisions, driving on narrow roads and recognizing traffic lights and speed limit signs.
(g) In 2015, China’s government launched two actions simultaneously i.e. the ‘Internet Plus’ and ‘Made in China
2025’ strategies. Ten major aspects in the sector of manufacturing are prioritized to boost the industrialization of
China (China State Council, 2015). In 2018, the Chinese government announced elimination of rules that required
car manufacturers such as General Motors to collaborate with a local company to open factories in China. China
anticipates the move will encourage foreign companies to bing more advanced technology into China to meet
demands for electric transportation.
(h) In 2016, the Singapore government launched its RIE 2020 Plan (Research, Innovation and Enterprise) with a
budget of $19 billion. The advanced manufacturing and engineering domain had identified eight key vertical
industries for the Plan (National Research Foundation 2016).In 2018, Singaporean companies are developing
machines that can help make slight tweaks to fully automate hydroponic farms and maximize crop yield.
(i) In Malaysia, the government aggressively took action by undertaking various efforts in helping industry
players to embrace Industry 4.0 through the implementation of automation and smart manufacturing. In Budget 2017,
the government highlighted several new incentive packages to accelerate the growth and adoption of manufacturing
and Industry 4.0 in Malaysia. For instance, Supermax Corporation Bhd. was a glove manufacturing industry which
under the automation and Industry 4.0 in manufacturing will be supported by the government through incentive
programmes to spur the growth of the industry. Former Prime Minister of Malaysia, Datuk Seri Najib Razak
initiated the government’s plan to implement TVET in industries. This is to assist the development of Industry 4.0 in
the future by increasing the capabilities of the workforce. Under this program, the government allocated RM50
million to improve the caliber and the competitiveness of the workforce to help in the economic development of the
nation. This budget is allocated from 30% of the Human Resources Development Fund (HRDF) funds specifically
for the purpose of TVET.
In short, the government’s plans above show that developing countries are significantly focused on the
advancement of technologies and the fact that industry 4.0 can bring many positive impacts to a nation’s
development. As the physical world, biological world and digital world keep on converging, advanced technologies
and phases will provide opportunities for citizens to interact with their government and voice their opinions and
even circumvent the supervision of oppressive public authorities.
VI.
Conclusion
In a nutshell, Industry 4.0 is the future of global manufacturing which aggregates existing ideas to a new value
chain which plays a crucial role to transform whole value chains of life cycle of goods while developing innovative
services and products in the manufacturing industry which involves the connection of systems to things that creates
self-organizing and dynamic control within an organization. Industry 4.0 describes a future scenario of industrial
production that is characterized by the aspects of a new level of controlling, organizing and transforming the entire
value chain with the life cycle of products,resulting in higher productivity and flexibility through three types of
effective integration which are horizontal, vertical and end-to-end engineering integration. Hence, these can predict
product performance degradation and autonomously manage and optimize product service needs and consumption
of resources which lead to optimization and reduction of costs. Next, the creation of dynamic, real-time optimized
and self-organizing cross-company value networks through the Cyber-Physical Systems(CPS), Internet of Things
Jour of Adv Research in Dynamical & Control Systems, Vol. 10, 14-Special Issue, 2018
ISSN 1943-023X
Received: 20 October 2018/Accepted: 15 November 2018
1386
(IoT), artificial intelligence (AI), additive manufacturing, cloud computing and others are added. It is hoped that
with the proper guidance and technical skills, more and more manufacturing companies in Malaysia will implement
Industry 4.0 in their business.
Acknowledgement
The authors gratefully acknowledge Universiti Tun Hussein Onn, Malaysia and Ministry of Higher Education for
the financial support provided for this research through Research Grant Scheme, TIER 1 Vot U880 and GPPS Vot
H044.
References
[1] Buxmann P., Hess T. and Rugabber R. Internet of Services. Business & Information Systems Engineering 5
(2) (2009).
[2] China. State Council SC. Made in China 2025: report. Beijing: State Council, 2015.
[3] Conseil national de l’ industrie. The New Face of Industry in France. Paris: French National Industry
Council, 2013.
[4] Dilberoglu, U. M., Gharehpapagh, B., Yaman, U. and Dolen, M.. The role of additive manufacturing in the
era of Industry 4 . 0. Procedia Manufacturing 11 (2) (2017) 545554.
[5] European Factories of the Future Research Association EFFRA. Factories of the future: multi-annual
roadmap for the contractual PPP under Horizon2020: report. Brussels: EFFRA, 2013.
[6] Foresight. The Future of Manufacturing: A New Era of Opportunity and Challenge for the UK. London:
UK Government Office for Science, 2013.
[7] Gorecky, D., Schmitt, M., Loskyll, M. and Zühlke, D. Human-Machine-Interaction in the Industry 4.0 Era.
12th IEEE International Conference on Industrial Infomatic, 2014, 289294.
[8] He, K.F. Cyber-Physical System for Maintenance in Industry 4.0. Jonkoping University: Master’s Thesis,
2016.
[9] Kagermann, H., Wahlster.W. and Johannes, H. Recommendations for Implementing the Strategic Initiative
INDUSTRIE 4.0. Forschungsunion, 2013.
[10] Liao, Y., Deschamps, F., Freitas, E.D. and Loures, R. Past, present and future of Industry 4.0 - a systematic
literature review and research agenda proposal. International Journal of Production Research 55 (12),
(2017) 36093629.
[11] Marcos, M., Suárez, S., Marcos, M., Fernández-miranda, S. S., Marcos, M., Peralta, M. E. and Aguayo, F.
The challenge of integrating Industry in the degree of Mechanical Engineering. Procedia Manufacturing 13
(1) (2017) 12291236.
[12] Masoni, R., Ferrise, F., Bordegoni, M., Gattullo, M., Uva, E., Fiorentino, M., Carrabba,E. and Donato,M.,.
Supporting remote maintenance in industry 4.0 through augmented reality. Procedia Manufacturing 11 (6)
(2017) 12961302.
[13] Ministry of Trade Industry and Energy of South Korea MOTIE. Manufacturing innovation 3.0 strategy
for the creation of economy. Sejong City, 2014.
[14] Mosterman, P. and Zender, J. Industry 4.0 as a Cyber-Physical System study Industry 4.0 as a Cyber-
Physical System study. Software & Systems Modeling 12 (2) (2015) 1-14.
[15] Mrugalska, B. and Wyrwicka, M.K. Towards Lean Production in Industry 4.0. Procedia Engineering 182
(2017) 466473.
[16] National Research Fountation Research, Innovation and Enterprise 2020 (RIE2020). Retrieved
from : http://www.nrf.gov.sg/rie2020, 2016.
[17] President’s Council of Advisors on Science and Technology – PCAST. Report to the president accelerating
U.S. advanced manufacturing. Washington: Executive Office of PCAST, 2014.
[18] Qin, J., Liu, Y. and Grosvenor, R. A Categorical Framework of Manufacturing for Industry 4.0 and Beyond.
Procedia CIRP, 2016, 173178.
[19] Rodič, B. Industry 4.0 and the New Simulation Modelling Paradigm, Organizacija 50 (3) (2017) 193207.
[20] Sangeetha, A. Malaysia’s Industry 4.0 initiative slow on uptake.The Edge Financial Daily. Retrieved
from http://www.theedgemarkets.com/article/malaysias-industry-40-initiative-slow-uptake, 2017.
[21] Schumacher, A., Erol, S. and Sihn, W. A maturity model for assessing Industry 4 . 0 readiness and maturity
of manufacturing enterprises. Procedia CIRP 52 (2016) 161166.
[22] Schwab, K. The Fourth Industrial Revolution, what it means and how to respond. Retrieved
from https://www.weforum.org/agenda/2016/01/the-fourth-industrial-revolution-what-it-means-and-how-
Jour of Adv Research in Dynamical & Control Systems, Vol. 10, 14-Special Issue, 2018
ISSN 1943-023X
Received: 20 October 2018/Accepted: 15 November 2018
1387
tores pond, 2016.
[23] Wang, S., Wan, J., Li, D. and Zhang, C. Implementing Smart Factory of Industrie 4.0 : An
Outlook,International Journal of Distributed Sensor Networks 6 (2) (2016) 1-10.
[24] Wiesner, S. A., Thoben, K., Wiesner, S. and Wuest, T. Industrie 4.0 " and Smart Manufacturing A
Review of Research Issues and Application Examples.International Journal of AutomationTechnologway
11 (1) (2017) 4-16.
[25] Witkowski, K. Internet of Things , Big Data , Industry 4.0 Innovative Solutions in Logistics and Supply
Chains Management. Procedia Engineering 182 (1) (2017) 763769.
[26] Xu, X. Robotics and Computer-Integrated Manufacturing From cloud computing to cloud manufacturing
Ubiquitous Product Life cycle Support. Robotics and Computer Integrated Manufacturing 28 (1) (2012)
7586.
[27] Zhong, R. Y., Xu, X., Klotz, E. and Newman, S. T. Intelligent Manufacturing in the Context of Industry
4.0 : A Review. Engineering 3 (5) (2017) 616630.
... These tendencies are in accordance with the emergence of industrial revolution 4.0 (IR 4.0) 6 marked by the industrial transformation manufacturing through digitalization and the potential new technologies exploitation (Rojko, 2017). In IR 4.0 era manufacturing sectors depend more on networked system which allows overall change in products, procedures and services (Halili et al., 2020;Tay, 2018). Therefore, digitalization in industries, education, and workplaces cannot be avoided. ...
Article
Full-text available
This research is aimed at investigating the implementation of project-based learning (PBL) using a voice recorder, Orai application, and web as material sources. It is conducted to determine the impact of combining PBL and digital tools on speaking performance. The participants were 80 students who took English subject in State Polytechnic of Malang, Electronic Engineering study program. Five aspects of speaking performance were observed to determine which ones are affected by the strategy. The research methodology employed was quasi-experimental with pre-test and post-test. Participants were selected via random sampling. The research sample consisted of two classes with the total sample of 80 students. Data analysis was done through hypothesis testing of the speaking performance data. The results showed that infusing digital technology into project-based learning can significantly improve speaking performance in the aspects of grammar, comprehension, and vocabulary, but does not significantly affect the fluency and pronunciation aspects. Advice and recommendations to the faculty and teacher candidates were discussed further.
... New leading automated technologies, such as cyber physical systems, the Internet of Things (IoT), artificial intelligence, machine learning, cloud computing, among others, will cause important changes in the configuration of the processes of work, a scenario known as Industry 4.0 (Tay, Lee, Hamid, & Ahmad, 2018). For instance, many organizations are working to harness these technologies through automation so they can vastly improve their production processes (Panigrahi, 2021). ...
Article
Full-text available
Purpose: To identify which psychosocial factors can be related to the increasing automation of work processes, determining practical implications relevant to the evaluation of psychosocial risk factors at work within organizations before the imminent transition towards industry 4.0 Design/methodology/approach: A systematic review of the literature was carried out. The review structure was based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach for the studies selection and the Noblit and Hare's meta-ethnographic approach for data analysis and synthesis. Findings: Thirty-five studies were selected which passed all the selection stages. Six psychosocial risk factors were detected whose behaviors may be influenced by the increasing automation of work. Evidence suggests that the factors of development possibility, change management, mental load, routine content, and job insecurity may increase their exposure due to job modifications owing to new automation technologies. On the other hand, social relationships at work have the ability to positively influence the successful implementation of new automated processes. Originality/value: The results obtained represent excellent indications of an overview of psychosocial risk factors that may increase their danger due to the increasing automation of work processes and Industry 4.0.
... IR 4.0 which includes industrial IoT and smart manufacturing, combines physical production and operations with smart digital technologies. Even though each business and organization today are different, they all confront the same problem, the need for connectivity and access to real-time data across partners, products, and people (Tay et al., 2018). IoT generally refers to scenarios where network connectivity and computing capability extends to objects, sensors and everyday items not normally considered computers, allowing these devices to generate, exchange and consume data with minimal human intervention. ...
... Digital twins (DT) have become a hot topic in recent years, gaining traction in both academic research and industrial applications [61]. This technology aligns perfectly with the innovative spirit of Industry 4.0, as it leverages automation tools and data exchange methods common in modern manufacturing, including the Internet of Things (IoT), cloud computing, cyber-physical systems (CPS), big data analytics, simulation, and augmented reality [62,63]. The surge in DT research is reflected in the growing number of review publications across diverse application areas. ...
Article
Full-text available
The economic growth of developed or emerging countries through globalization has prompted them to increase their supply chain performance. A large number of concepts, tools, and methodologies have been proposed in support of this performance improvement. They are mainly based on the use of classical optimization or enterprise modeling methods. However, environmental and social issues, not to mention digital transformation, are often ignored or not sufficiently integrated. Indeed, the world geopolitical situation, the increase in oil prices, and the commitment to protect our earth require the integration of sustainability aspects and Industry 4.0 concepts like digital twin and artificial intelligence in transforming the supply chain. This paper focuses on defining a conceptual framework to support sustainable supply chain management and digital transformation. It aims to exploit the sustainability and digital maturity of companies to transform their supply chains and enhance their performance to meet the challenges of Industry 5.0. Several practices related to sustainability, as well as two use cases on optimization and digital twin, are presented to illustrate this framework. Finally, based on the previous practices and use cases, an adapted framework for the supply chain manager to support the transition from Industry 4.0 to Industry 5.0 has been developed, as well as a performance dashboard.
... Since 2011, there has been a terminological definition of "Industry 4.0", which is the natural successor of the previous industrial revolutions. About "Industry 4.0" various authors said that it is the future of global production that unites existing ideas and new values in a chain that plays a key role in transforming the entire value of the life cycle of goods in one innovative form, resulting in greater productivity and flexibility of engineering integration (Tay et al. 2018). ...
Article
Full-text available
As a rule, the directions of development of the national security strategy are always aligned with vital national interests and modern achievements of society, which are imbued with modern challenges, risks and threats and available instruments of power. Monitoring global trends and the use of an adequate methodological approach enables the strategy to reflect a clear definition of national interests, ways of achieving them and the state's ability to achieve those interests using instruments of national power. Artificial intelligence through various forms of manifestation will significantly influence the development of future society. The implementation methodology will depend primarily on the needs and capabilities of the state. The goal of this work is to bring artificial intelligence closer to the professional public and to somehow place it in the focus of future considerations in the field of security and defense. Technology, which every day is becoming more and more present in all spheres of life, must find its role and place in strategic and doctrinal documents related to the defense of the state. Artificial intelligence must be integrated and operationalized as one of the starting points for creating a modern national security strategy, which is also the thesis of this expert work. The thesis clearly implies that the future national security strategy cannot be conceived without the concept of using artificial intelligence. The theoretical foundation of artificial intelligence is imbued in various scientific fields that primarily deal with automation and autonomous use of systems. Practical application found its basis in the gradual but comprehensive digitization of all spheres of life and society as a whole. From the point of view of national security, it is especially important to consider the impact in the development of autonomous weapon systems, the perspective of their use and the way they will shape modern armed conflicts.
Article
This empirical study delves into the implementation of Industry 4.0 within organizations in Poland, with a particular focus on the impact of advanced technologies. The research challenges the prevailing notion that larger organizations are more adept at adopting Industry 4.0, while also investigating the levels of agility and adaptation among smaller entities. The study evaluates four research hypotheses by analyzing data collected from 73 organizations in Poland. Special attention is given to a comprehensive assessment of Industry 4.0 implementation, emphasizing advanced technologies such as augmented reality, artificial intelligence, and robotics. Contrary to common belief, the findings indicate that smaller organizations often demonstrate higher levels of agility and adaptation in implementing certain aspects of Industry 4.0 compared to their larger counterparts. Despite widespread awareness of Industry 4.0 concepts, a notable gap exists between awareness and effective implementation. Notably, cybersecurity emerges as the most successfully implemented area, likely due to an increased awareness of digital threats. However, other technologies like augmented reality, AI, and robotics exhibit lower implementation levels, suggesting practical application barriers. The study further reveals varying levels of readiness among different sectors to embrace new technologies.
Research
Full-text available
Embedded systems, integral in numerous industries, confront escalating cybersecurity threats due to interconnectivity and limited computational resources. This paper advocates a proactive 'Software-First Approach' to mitigate cybersecurity risks in embedded systems. Focusing on software-centric security measures throughout system design, development, and deployment, this approach aligns with evolving threats while accommodating resource constraints. Key aspects encompass secure coding practices, robust software architecture, continuous monitoring, and adaptive defense mechanisms. The paper delves into integrating threat modeling, vulnerability assessments, and secure software development life cycles to fortify systems. A specific focus lies in implementing machine learning algorithms like XGBoost and neural networks for anomaly detection, augmenting traditional security practices. A case study demonstrates the efficacy of these strategies in bolstering the security posture of an embedded system against diverse threats. Findings highlight the success of software-focused strategies in mitigating vulnerabilities, reducing attack surfaces, and enhancing resilience against evolving cyber threats, showcasing the effectiveness of software-centric approaches bolstered by machine learning algorithms in safeguarding embedded systems.
Article
Full-text available
Our next generation of industry—Industry 4.0—holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. Intelligent manufacturing plays an important role in Industry 4.0. Typical resources are converted into intelligent objects so that they are able to sense, act, and behave within a smart environment. In order to fully understand intelligent manufacturing in the context of Industry 4.0, this paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things (IoT)-enabled manufacturing, and cloud manufacturing. Similarities and differences in these topics are highlighted based on our analysis. We also review key technologies such as the IoT, cyber-physical systems (CPSs), cloud computing, big data analytics (BDA), and information and communications technology (ICT) that are used to enable intelligent manufacturing. Next, we describe worldwide movements in intelligent manufacturing, including governmental strategic plans from different countries and strategic plans from major international companies in the European Union, United States, Japan, and China. Finally, we present current challenges and future research directions. The concepts discussed in this paper will spark new ideas in the effort to realize the much-anticipated Fourth Industrial Revolution.
Article
Full-text available
Industry is facing a historic turning point [1]. In industry 4.0, people, machines and products communicate with one another via the internet. This means the convergence of industry and Internet technology. Modern machines allow companies to exploit the potential of digitalization in their production facilities and to unlock new business fields. The mechanical engineering sector have to know how new technologies can be successfully integrated for the benefit of the customer. Production processes and supply chains will become more efficient, with advances in productivity and huge savings in material and energy. Digitalization goes hand in hand with the growing importance of platforms for data exchange, customer contact and services. Online platforms facilitate market access, reduce transaction costs and enable innovation through new business models. Machines are connected around the world, so Industry 4.0 would not be possible without networks and data traffic.
Article
Full-text available
The latest industrial revolution, Industry 4.0, is encouraging the integration of intelligent production systems and advanced information technologies. Additive manufacturing (AM) is considered to be an essential ingredient in this new movement. In this paper, a comprehensive review on AM technologies is presented together with both its contributions to Industry 4.0. The review focusses on three important aspects of AM: recent advances on material science, process development, and enhancements on design consideration. The main objective of the paper is to classify the current knowledge (and technological trends) on AM and to highlight its potential uses.
Article
Full-text available
Due to the Industry 4.0 initiative, Augmented Reality (AR) has started to be considered one of the most interesting technologies companies should invest in, especially to improve their maintenance services. Several technological limitations have prevented AR to become an effective industrial tool in the past. Now some of them have been overcome, some others not yet by off-the-shelf technologies. In this paper, we present a solution for remote maintenance based on off-the-shelf mobile and AR technologies. The architecture of the application allows us to remotely connect a skilled operator in a control room with an unskilled one located where the maintenance task has to be performed. This application, which has been initially described in a previous work, has been improved on the basis of feedback received by industrial partners. We describe the important features we have added and the rationale behind them to make the remote communication more effective.
Article
Full-text available
The aim of this paper is to present the influence of Industry 4.0 on the development of the new simulation modelling paradigm, embodied by the Digital Twin concept, and examine the adoption of the new paradigm via a multiple case study involving real-life R&D cases involving academia and industry. : We introduce the Industry 4.0 paradigm, presents its background, current state of development and its influence on the development of the simulation modelling paradigm. Further, we present the multiple case study methodology and examine several research and development projects involving automated industrial process modelling, presented in recent scientific publications and conclude with lessons learned. We present the research problems and main results from five individual cases of adoption of the new simulation modelling paradigm. Main lesson learned is that while the new simulation modelling paradigm is being adopted by big companies and SMEs, there are significant differences depending on company size in problems that they face, and the methodologies and technologies they use to overcome the issues. While the examined cases indicate the acceptance of the new simulation modelling paradigm in the industrial and scientific communities, its adoption in academic environment requires close cooperation with industry partners and diversification of knowledge of researchers in order to build integrated, multi-level models of cyber-physical systems. As shown by the presented cases, lack of tools is not a problem, as the current generation of general purpose simulation modelling tools offers adequate integration options.
Article
Full-text available
The aim of this article is to present some ‘smart’ solutions which could be recognised as innovative solutions in both areas: technology and organisation. The above mentioned solutions could be implemented by logistics which, in the era of globalization, plays a very important role. This applies not only to functioning of individual companies, but also to national economies and even the world economy. The phenomenon of competition can now be observed not just in individual companies but in entire supply chains. The pace of development of the modern economy means that companies are forced to constantly introduce more and more new solutions, resulting in innovation driving the progress of the market. This article is a part of research, which considers the problem of implementation of IT solutions logistics.
Article
Full-text available
Best Paper Award 2018 of IJPR (55th Volume Anniversary: 15 Free to Access Papers IJPR) It was made free to access for the duration of 2018, exclusively via this page: http://explore.tandfonline.com/content/est/tprs-55-anniv?utm_source=TFO&utm_medium=cms&utm_campaign=JMQ04737
Article
Full-text available
**** '2017 IJAT Best Review Paper Award' for the most prominent review paper in recent years published in the International Journal of Automation Technology (IJAT). **** A fourth industrial revolution is occurring in global manufacturing. It is based on the introduction of Internet of things and servitization concepts into manufacturing companies, leading to vertically and horizontally integrated production systems. The resulting smart factories are able to fulfill dynamic customer demands with high variability in small lot sizes while integrating human ingenuity and automation. To support the manufacturing industry in this conversion process and enhance global competitiveness, policy makers in several countries have established research and technology transfer schemes. Most prominently, Germany has enacted its Industrie 4.0 program , which is increasingly affecting European policy, while the United States focuses on smart manufacturing. Other industrial nations have established their own programs on smart manufacturing, notably Japan and Korea. This shows that manufacturing intelligence has become a crucial topic for researchers and industries worldwide. The main object of these activities are the so-called cyber-physical systems (CPS): physical entities (e.g., machines, vehicles, and work pieces), which are equipped with technologies such as RFIDs, sensors, microprocessors, telematics or complete embedded systems. They are characterized by being able to collect data of themselves and their environment , process and evaluate these data, connect and communicate with other systems, and initiate actions. In addition, CPS enabled new services that can replace traditional business models based solely on product sales. The objective of this paper is to provide an overview of the Industrie 4.0 and smart manufacturing programs, analyze the application potential of CPS starting from product design through production and logistics up to maintenance and exploitation (e.g., recycling), and identify current and future research issues. Besides the technological perspective, the paper also takes into account the economic side considering the new business strategies and models available.
Article
Full-text available
Manufacturing enterprises are currently facing substantial challenges with regard to disruptive concepts such as the Internet of Things, Cyber Physical Systems or Cloud-based Manufacturing – also referred to as Industry 4.0. Subsequently, increasing complexity on all firm levels creates uncertainty about respective organizational and technological capabilities and adequate strategies to develop them. In this paper we propose an empirically grounded novel model and its implementation to assess the Industry 4.0 maturity of industrial enterprises in the domain of discrete manufacturing. Our main goal was to extend the dominating technology focus of recently developed models by including organizational aspects. Overall we defined 9 dimensions and assigned 62 items to them for assessing Industry 4.0 maturity. The dimensions “Products”, “Customers”, “Operations” and “Technology” have been created to assess the basic enablers. Additionally, the dimensions “Strategy”, “Leadership”, Governance, “Culture” and “People” allow for including organizational aspects into the assessment. Afterwards, the model has been transformed into a practical tool and tested in several companies whereby one case is presented in the paper. First validations of the model's structure and content show that the model is transparent and easy to use and proved its applicability in real production environments.