Industry 4.0: A Proposal of Paradigm Organization Schemes from a Systematic Literature Review

Currently, the concept of Industry 4.0 is well known; however, it is extremely complex, as it is constantly evolving and innovating. It includes the participation of many disciplines and areas of knowledge as well as the integration of many technologies, both mature and emerging, but working in collaboration and relying on their study and implementation under the novel criteria of Cyber–Physical Systems. This study starts with an exhaustive search for updated scientific information of which a bibliometric analysis is carried out with results presented in different tables and graphs. Subsequently, based on the qualitative analysis of the references, we present two proposals for the schematic analysis of Industry 4.0 that will help academia and companies to support digital transformation studies. The results will allow us to perform a simple alternative analysis of Industry 4.0 to understand the functions and scope of the integrating technologies to achieve a better collaboration of each area of knowledge and each professional, considering the potential and limitations of each one, supporting the planning of an appropriate strategy, especially in the management of human resources, for the successful execution of the digital transformation of the industry.

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Engineering human-focused Industrial Cyber-Physical Systems in Industry 4.0 context

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2020.0366 ◽

2021 ◽

Vol 379 (2207) ◽

pp. 20200366

Author(s):

Armando Walter Colombo ◽

Stamatis Karnouskos ◽

Christoph Hanisch

Keyword(s):

Industry 4.0 ◽

Autonomous Systems ◽

Cyber Physical Systems ◽

Digital Transformation ◽

Three Dimensions ◽

Paradigm Change ◽

Reference Architecture ◽

Physical Systems ◽

Architecture Model ◽

Industrial Ecosystem

The world is increasingly interconnected, and this can also be seen in industry, where an ecosystem of digitalized assets, and humans with appropriate digital interfaces, constantly interact with each other. Digital transformation efforts in the industry rely on Industrial Cyber-Physical Systems that are driven by service-based cooperation among humans and digitalized industrial assets. This implies a radical paradigm change in their engineering and operation, which is focused on the symbiosis of digitalized assets and humans that cohabit a collaboration-driven industrial ecosystem. This work discusses how a digital transformation can effectively be achieved in an industrial ecosystem via a digitalization process performed along the three dimensions of the Reference Architecture Model for Industry 4.0, facilitated by the specification, development and implementation of an Asset Administration Shell. The discussion focus is put on humans and how the digitally transformed industrial environments empower her/his capabilities and interactions. It is also critically pointed out how one should go beyond technology and consider additional aspects. Therefore, it is argued that human-centred efforts in Industry 4.0 (I4.0) should be seen in the larger context of sustainability and circular economy in order to properly consider the interplay of the involved socio-technical dimensions. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

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The Impact of Digital Transformation on Business Performance: A Study of Pakistani SMEs

Engineering, Technology & Applied Science Research ◽

10.48084/etasr.3201 ◽

2019 ◽

Vol 9 (6) ◽

pp. 5056-5061 ◽

Cited By ~ 1

Author(s):

M. F. Mubarak ◽

F. A. Shaikh ◽

M. Mubarik ◽

K. A. Samo ◽

S. Mastoi

Keyword(s):

Big Data ◽

Internet Of Things ◽

Industry 4.0 ◽

Business Performance ◽

Positive Impact ◽

Cyber Physical Systems ◽

Digital Transformation ◽

Infrastructure Development ◽

Physical Systems ◽

The Impact

Business ecosystems are continuously evolving. In this hyper-competitive era, firms are increasingly transforming their business operations through advanced digital technologies. Gone are the days of mere testing and debating the influence of digital transformation and industry 4.0, yet the time has come for actionable steps. Therefore, this study has identified the role of industry 4.0 technologies including big data, cyber-physical systems, internet of things and interoperability, on the performance of Small and Medium-sized Enterprises (SMEs) in Pakistan. A relevant questionnaire was developed and distributed randomly in the cities of Karachi, Lahore, Peshawar, Islamabad, Gujrat, and Sialkot. After applying multiple regression techniques through SPSS, it was found that big data, cyber-physical systems, and interoperability have a significant positive impact to improve business performance, while the insignificant effect of internet of things was revealed. Since the research in the area of digital transformation and industry 4.0 is scant, the current study has contributed novel directions, insights and a framework for future researchers. Moreover, this study will help managers to justify the allocation of resources towards technological infrastructure development in the operations of their firms. Finally, policymakers will find it helpful in order to devise suitable strategies for developing human capital and to enhance their absorptive capacity.

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ANALYSIS OF PROSPECTS AND OPPORTUNITIES OF CYBER-PHYSICAL SYSTEMS EDUCATION

Proceedings of CBU in Natural Sciences and ICT ◽

10.12955/pns.v1.122 ◽

2020 ◽

Vol 1 ◽

pp. 60-65

Author(s):

Galina Nikolcheva

Keyword(s):

Industry 4.0 ◽

Cyber Physical Systems ◽

Industrial Applications ◽

Digital Transformation ◽

Cyber Physical System ◽

Pilot Projects ◽

Laboratory Practice ◽

Good Practices ◽

Physical Systems ◽

Industry Standards

The readiness for digital transformation of industry is highly dependent from the existence of enough ICT experts with profiles to industrial applications and cyber-physical systems as well as the widespread promotion and application of existing industry standards and practices in the domain of Industry 4.0. The raising of the digital readiness index for the industry requires the development of educational and scientific initiatives in order to create capacity for institutional and organizational acceptance of the requirements and prerequisites of Industry 4.0 as well the creation of pilot projects and demonstration installations for the purpose of visualizing and presenting good practices. This paper analyses prospects and opportunities of Cyber-physical system education in order to prepare well-trained and capable specialists for Industry 4.0. Some good practices in this area are outlined. Ideas for building the foundation of the training as well as the organization of the laboratory practice are presented.

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Cyber-Physical Systems, Internet of Things, and Big Data in Industry 4.0: Digital Manufacturing Technologies, Business Process Optimization, and Sustainable Organizational Performance

Economics Management and Financial Markets ◽

10.22381/emfm14320193 ◽

2019 ◽

Vol 14 (3) ◽

pp. 23

Keyword(s):

Big Data ◽

Internet Of Things ◽

Organizational Performance ◽

Process Optimization ◽

Industry 4.0 ◽

Cyber Physical Systems ◽

Digital Manufacturing ◽

Physical Systems ◽

Manufacturing Technologies ◽

Business Process Optimization

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The challenges, approaches, and used techniques of CPS for manufacturing in Industry 4.0: a literature review

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-020-06572-4 ◽

2021 ◽

Vol 113 (7-8) ◽

pp. 2395-2412

Author(s):

Baudouin Dafflon ◽

Nejib Moalla ◽

Yacine Ouzrout

Keyword(s):

Internet Of Things ◽

Industry 4.0 ◽

Cyber Physical Systems ◽

Review Literature ◽

Comprehensive Understanding ◽

Physical Systems ◽

Fine Grained ◽

Key Technologies ◽

Granularity Level ◽

Human Component

AbstractThis work aims to review literature related to the latest cyber-physical systems (CPS) for manufacturing in the revolutionary Industry 4.0 for a comprehensive understanding of the challenges, approaches, and used techniques in this domain. Different published studies on CPS for manufacturing in Industry 4.0 paradigms through 2010 to 2019 were searched and summarized. We, then, analyzed the studies at a different granularity level inspecting the title, abstract, and full text to include in the prospective study list. Out of 626 primarily extracted relevant articles, we scrutinized 78 articles as the prospective studies on CPS for manufacturing in Industry 4.0. First, we analyzed the articles’ context to identify the major components along with their associated fine-grained constituents of Industry 4.0. Then, we reviewed different studies through a number of synthesized matrices to narrate the challenges, approaches, and used techniques as the key-enablers of the CPS for manufacturing in Industry 4.0. Although the key technologies of Industry 4.0 are the CPS, Internet of Things (IoT), and Internet of Services (IoS), the human component (HC), cyber component (CC), physical component (PC), and their HC-CC, CC-PC, and HC-PC interfaces need to be standardized to achieve the success of Industry 4.0.

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Artificial Intelligence and the Internet of Things in Industry 4.0

CCF Transactions on Pervasive Computing and Interaction ◽

10.1007/s42486-021-00057-3 ◽

2021 ◽

Author(s):

Petar Radanliev ◽

David De Roure ◽

Razvan Nicolescu ◽

Michael Huth ◽

Omar Santos

Keyword(s):

Artificial Intelligence ◽

Internet Of Things ◽

Industry 4.0 ◽

Cyber Physical Systems ◽

Physical Systems ◽

Leading Industry ◽

Key Technologies ◽

The Internet Of Things ◽

State Of Art ◽

Social Level

AbstractThis paper presents a new design for artificial intelligence in cyber-physical systems. We present a survey of principles, policies, design actions and key technologies for CPS, and discusses the state of art of the technology in a qualitative perspective. First, literature published between 2010 and 2021 is reviewed, and compared with the results of a qualitative empirical study that correlates world leading Industry 4.0 frameworks. Second, the study establishes the present and future techniques for increased automation in cyber-physical systems. We present the cybersecurity requirements as they are changing with the integration of artificial intelligence and internet of things in cyber-physical systems. The grounded theory methodology is applied for analysis and modelling the connections and interdependencies between edge components and automation in cyber-physical systems. In addition, the hierarchical cascading methodology is used in combination with the taxonomic classifications, to design a new integrated framework for future cyber-physical systems. The study looks at increased automation in cyber-physical systems from a technical and social level.

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Reliable Industry 4.0 Based on Machine Learning and IoT for Analyzing, Monitoring, and Securing Smart Meters

Sensors ◽

10.3390/s21020487 ◽

2021 ◽

Vol 21 (2) ◽

pp. 487 ◽

Cited By ~ 2

Author(s):

Mahmoud Elsisi ◽

Karar Mahmoud ◽

Matti Lehtonen ◽

Mohamed M. F. Darwish

Keyword(s):

Machine Learning ◽

Smart Grids ◽

Industry 4.0 ◽

Learning Algorithm ◽

Cyber Physical Systems ◽

The Internet ◽

Smart Meters ◽

Industrial Environment ◽

Physical Systems ◽

Smart Machines

The modern control infrastructure that manages and monitors the communication between the smart machines represents the most effective way to increase the efficiency of the industrial environment, such as smart grids. The cyber-physical systems utilize the embedded software and internet to connect and control the smart machines that are addressed by the internet of things (IoT). These cyber-physical systems are the basis of the fourth industrial revolution which is indexed by industry 4.0. In particular, industry 4.0 relies heavily on the IoT and smart sensors such as smart energy meters. The reliability and security represent the main challenges that face the industry 4.0 implementation. This paper introduces a new infrastructure based on machine learning to analyze and monitor the output data of the smart meters to investigate if this data is real data or fake. The fake data are due to the hacking and the inefficient meters. The industrial environment affects the efficiency of the meters by temperature, humidity, and noise signals. Furthermore, the proposed infrastructure validates the amount of data loss via communication channels and the internet connection. The decision tree is utilized as an effective machine learning algorithm to carry out both regression and classification for the meters’ data. The data monitoring is carried based on the industrial digital twins’ platform. The proposed infrastructure results provide a reliable and effective industrial decision that enhances the investments in industry 4.0.

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Introducing Gamification in the AR-Enhanced Order Picking Process: A Proposed Approach

Logistics ◽

10.3390/logistics5010014 ◽

2021 ◽

Vol 5 (1) ◽

pp. 14

Author(s):

Athina G. Bright ◽

Stavros T. Ponis

Keyword(s):

Industry 4.0 ◽

Business Processes ◽

Cyber Physical Systems ◽

Order Picking ◽

Physical Systems ◽

The Core ◽

Complex Process ◽

Core Elements ◽

Game Elements ◽

Innovative Industry

In the last decade, the Industry 4.0 concept has introduced automation and cyber-physical systems as the core elements of future logistics, supported by an array of technologies, such as augmented reality (AR) providing the necessary support for the digital transformation of manufacturing and logistics and the smartification and digital refinement of traditional pre-Industry 4.0 processes. This paper studies the influence and the potential of gamification techniques in supporting innovative Industry 4.0-enhanced processes in the contemporary warehouse work ecosystem. Gamification in the workplace aims to motivate the employees and increase their involvement in an activity, while at the same time creating a sense of an everyday different experience rather than a set of repetitive and monotonous tasks. Since the design of such a system is a complex process, the most widespread design frameworks are studied, and the emphasis is on the principal game elements and their connection to mobilization mechanisms. Finally, an initial proposal of a gamification framework to support the AR-enhanced order picking process in contemporary logistics centers is provided with an emphasis on the mechanics of a fair and functional reward system. The proposed approach aims to showcase the potential alignment of business processes to human motivation, respecting the differences between tasks and the workers’ cognitive workload.

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