“Industry 4.0” Digital Strategy, and the Challenges for Adoption the Technologies Led by Cyber-Physical Systems

2020 ◽  
pp. 463-472
Author(s):  
Fernando Lima da Silva ◽  
Gladys Dorotea Cacsire Barriga
Keyword(s):  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Digital Strategy

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

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.

scholarly journals Artificial Intelligence and the Internet of Things in Industry 4.0

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.

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

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 487 ◽  
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.

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

Logistics ◽  
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.

Cyber-physical systems architectures for industrial internet of things applications in Industry 4.0: A literature review

2021 ◽  
Vol 58 ◽  
pp. 176-192
Author(s):  
Diego G.S. Pivoto ◽  
Luiz F.F. de Almeida ◽  
Rodrigo da Rosa Righi ◽  
Joel J.P.C. Rodrigues ◽  
Alexandre Baratella Lugli ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Literature Review ◽  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Industrial Internet Of Things ◽  
Physical Systems ◽  
Industrial Internet ◽  
Systems Architectures

scholarly journals Effects of Industry 4.0 on the Labor Markets of Iran and Japan

Economies ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 39 ◽  
Author(s):  
Majid Ziaei Nafchi ◽  
Hana Mohelská
Keyword(s):  
Labor Markets ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
Developed Countries ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Science Technology ◽  
Levels Of Automation ◽  
Technology And Economy ◽  
The Impact

Industry 4.0 is the essence of the fourth Industrial revolution and is happening right now in manufacturing by using cyber-physical systems (CPS) to reach high levels of automation. Industry 4.0 is especially beneficial in highly developed countries in terms of competitive advantage, but causes unemployment because of high levels of automation. The aim of this paper is to find out if the impact of adopting Industry 4.0 on the labor markets of Iran and Japan would be the same, and to make analysis to find out whether this change is possible for Iran and Japan with their current infrastructures, economy, and policies. With the present situation of Iran in science, technology, and economy, it will be years before Iran could, or better say should, implement Industry 4.0. Japan is able to adopt Industry 4.0 much earlier than Iran and with less challenges ahead; this does not mean that the Japanese labor market would not be affected by this change but it means that those effects would not cause as many difficulties as they would for Iran.

scholarly journals Automotive Industry in the Context of Industry 4.0 Strategy

2018 ◽  
Vol 13 (2) ◽  
pp. 61-65
Author(s):  
Juraj Sinay ◽  
Zuzana Kotianová
Keyword(s):  
Change Management ◽  
Automotive Industry ◽  
Driving Force ◽  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
On Line

Abstract The emergence of cyber-physical systems encourages constant adaptation to the complex requirements of new systems, creating new requirements for businesses that must adapt their activity to change. The automotive industry is the decisive industry and the driving force behind the development of the Slovak economy. Changes that have occurred in the automotive industry are reflected in the high automation of processes, which is reflected in the need to change management, in particular the need for on-line automotive tracking.

scholarly journals How connectivity and search for producers impact production in Industry 4.0 networks

2018 ◽  
Vol 15 (4) ◽  
pp. 528-534
Author(s):  
Adriano Pereira ◽  
Eugênio De Oliveira Simonetto ◽  
Goran Putnik ◽  
Helio Cristiano Gomes Alves de Castro
Keyword(s):  
Industry 4.0 ◽  
Industrial Revolution ◽  
Cyber Physical Systems ◽  
Average Degree ◽  
Collaborative Networks ◽  
Production Network ◽  
Simulation Environment ◽  
Physical Systems ◽  
Study Results ◽  
The Internet Of Things

Technological evolutions lead to changes in production processes; the Fourth Industrial Revolution has been called Industry 4.0, as it integrates Cyber-Physical Systems and the Internet of Things into supply chains. Large complex networks are the core structure of Industry 4.0: any node in a network can demand a task, which can be answered by one node or a set of them, collaboratively, when they are connected. In this paper, the aim is to verify how (i) network's connectivity (average degree) and (ii) the number of levels covered in nodes search impacts the total of production tasks completely performed in the network. To achieve the goal of this paper, two hypotheses were formulated and tested in a computer simulation environment developed based on a modeling and simulation study. Results showed that the higher the network's average degree is (their nodes are more connected), the greater are the number of tasks performed; in addition, generally, the greater are the levels defined in the search for nodes, the more tasks are completely executed. This paper's main limitations are related to the simulation process, which led to a simplification of production process. The results found can be applied in several Industry 4.0 networks, such as additive manufacturing and collaborative networks, and this paper is original due to the use of simulation to test this kind of hypotheses in an Industry 4.0 production network.

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