Modelling and quantification of industry 4.0 manufacturing complexity based on information theory: a robotics case study

Mourtzis, Dimitris; Fotia, Sophia; Boli, Nikoletta; Vlachou, Ekaterini

doi:10.1080/00207543.2019.1571686

Cited by 80 publications

(47 citation statements)

References 20 publications

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“…However, utilization of Industry 4.0 technologies also triggered increased energy consumption from sensors and machinery [14]. All the pros and cons of Industry 4.0 opened up new questions; for instance, what are the steps on the path towards Industry 4.0 adoption, or how would the implementation of enabling technologies impact their existing operations [3,15].…”

Section: Literature Reviewmentioning

confidence: 99%

“…To achieve sustainability and further develop their business, manufacturing companies need to find an appropriate response to the previously mentioned issues in a way that will increase efficiency, reduce costs, improve agility and flexibility, and upgrade responsiveness and resilience of their production operations [2]. For many manufacturing companies, it seems that the answer lies in the adoption of the Industry 4.0 paradigm [3]. This implies building an interface between the physical and the digital space through the use of Industry 4.0 enabling technologies such as Cyber-Physical Systems (CPS), Internet of Things (IoT), Cloud Computing (CC), Big Data, and Data Science [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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A Precondition of Sustainability: Industry 4.0 Readiness

2021

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To achieve sustainability and further develop their businesses, manufacturing companies need to find an appropriate response to the frequent changes in customer demands, development of new technologies, and dynamic competition. One of the possible requirements for sustainability is the adoption of the Industry 4.0 paradigm. This paper aims to apply Industry 4.0 general readiness assessment methodology and social network analysis to find out the readiness level of Serbian manufacturing and how digital technologies interplay during the time. The results of this study show that wireless human-machine communication technologies initiated the digital transformation of Serbian manufacturing from non-users to basic readiness level. Secondly, manufacturing companies significantly invested in the Cyber-Physical Production System to increase the level towards high readiness. Finally, manufacturing companies in Serbia should consider investing in capabilities to adapt the Near real-time production control system if aiming to compete with competitors from developed countries. The main contribution of this paper is to show the general readiness level of manufacturing companies for digital transformation in transition economies.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Precondition of Sustainability: Industry 4.0 Readiness

2021

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“…Actually, industry 4.0 is increasingly being promoted as the key to improving productivity, promoting economic growth and ensuring the sustainability of manufacturing companies [21][22][23]. Moreover, it aims to improve the flexibility, adaptability, and resilience of the industrial systems [24,25]. Industry 4.0 has been considered a new industrial stage in which several emerging or disruptive technologies including Internet of things (IoT), Artificial intelligence (AI), 3D printing and Big Data are converging to provide digital solutions [26,27].…”

Section: Introductionmentioning

confidence: 99%

The Hype and Disruptive Technologies of Industry 4.0 in Major Industrial Sectors: A State of the Art

Bongomin¹,

Yemane²,

Kembabazi³

et al. 2020

Preprint

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Very well into the dawn of the fourth industrial revolution (industry 4.0), we hardly distinguish between what is artificial and what is natural (e.g. man-made virus and natural virus). Thus, the level of discombobulation among people, companies or countries is indeed unprecedented. The fact that industry 4.0 is explosively disrupting or retrofitting each and every industrial sector, makes industry 4.0 the famous buzzword amongst researchers today. However, the insight of industry 4.0 disruption in the industrial sectors remains ill-defined in both academic and non-academic literature. The present study aimed at identifying industry 4.0 neologisms, understanding the industry 4.0 disruption and illustrating the disruptive technologies convergence in the major industrial sectors. A total of 99 neologisms of industry 4.0 were identified. Industry 4.0 disruption in Education industry (Education 4.0), Energy industry (Energy 4.0), Agriculture industry (Agriculture 4.0), Healthcare industry (Healthcare 4.0), and Logistics industry (Logistics 4.0) are described. The convergence of 12 disruptive technologies including 3D printing, Artificial intelligence, Augmented reality, Big Data, Blockchain, Cloud computing, Drones, Internet of things, Nanotechnology, Robotics, Simulation and Synthetic biology in agriculture, healthcare and logistics industries are illustrated.

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“…system-level complexity can be attributed to this kind of inevitable unpredictability [10], [11]. Many integrated manufacturing systems, which are designed to be effective, are actually constrained by the system complexity to be ineffective [12], [13].…”

Section: Introductionmentioning

confidence: 99%

Linking Emergence to the Complex Product System

Wang

Binxiu

et al. 2020

IEEE Access

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The increasing complexity of product calls for manufacturing integration, while in turn high integration brings the problems of system level complexity. This paper proposes that complex product system (CoPS) should be managed as a dynamical system. The dynamical characteristics of CoPS are discussed from the perspective of emergence. A conceptual model is established to analyze the cause, process and result of the CoPS emergence. The mechanism of inner state emergence in CoPS is interpreted by formal languages to provide a point view of state space. It is concluded that the behavior of CoPS, especially the complexity, exhibits the 'entity is greater than the sum of the parts' phenomena when satisfying given necessary conditions. A novel methodology is then established to evaluate this emergence-based complexity. The feasibility and application of the novel complexity measurement is verified by an example of turbine housing production process. Further discussions are made on how to manage the potential emerging complexity based on the proposed measurement.

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Modelling and quantification of industry 4.0 manufacturing complexity based on information theory: a robotics case study

Cited by 80 publications

References 20 publications

A Precondition of Sustainability: Industry 4.0 Readiness

A Precondition of Sustainability: Industry 4.0 Readiness

The Hype and Disruptive Technologies of Industry 4.0 in Major Industrial Sectors: A State of the Art

Linking Emergence to the Complex Product System

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