Guest Editorial Industry 4.0–Prerequisites and Visions

Vogel‐Heuser, Birgit; Hess, Dieter

doi:10.1109/tase.2016.2523639

Cited by 299 publications

(133 citation statements)

References 6 publications

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“…Although there are several definitions of Industry 4.0, most of them agree that CPS is a design principle [14]. To succeed with Industry 4.0, an architecture for cyber physical production control has been constructed [15].…”

Section: Maintenance In Industry 40mentioning

confidence: 99%

Deep digital maintenance

2017

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With the emergence of Industry 4.0, maintenance is considered to be a specific area of action that is needed to successfully sustain a competitive advantage. For instance, predictive maintenance will be central for asset utilization, service, and after-sales in realizing Industry 4.0. Moreover, artificial intelligence (AI) is also central for Industry 4.0, and offers data-driven methods. The aim of this article is to develop a new maintenance model called deep digital maintenance (DDM). With the support of theoretical foundations in cyber-physical systems (CPS) and maintenance, a concept for DDM is proposed. In this paper, the planning module of DDM is investigated in more detail with realistic industrial data from earlier case studies. It is expected that this planning module will enable integrated planning (IPL) where maintenance and production planning can be more integrated. The result of the testing shows that both the remaining useful life (RUL) and the expected profit loss indicator (PLI) of ignoring the failure can be calculated for the planning module. The article concludes that further research is needed in testing the accuracy of RUL, classifying PLI for different failure modes, and testing of other DDM modules with industrial case studies.

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Section: Maintenance In Industry 40mentioning

confidence: 99%

Deep digital maintenance

2017

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“…In their perspective on Industry 4.0, Vogel-Heuser and Hess identify a set of challenges for the domain [21]. In particular, they identify challenges for software engineering that are well-known to the modeling community:…”

Section: Related Workmentioning

confidence: 99%

A Systematic Mapping Study on Modeling for Industry 4.0

Wortmann

Combemale

Barais

2017

2017 ACM/IEEE 20th International Conference on Model Driven Engineering Languages and Systems (MODELS)

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Industry 4.0 is a vision of manufacturing in which smart, interconnected production systems optimize the complete value-added chain to reduce cost and time-to-market. At the core of Industry 4.0 is the smart factory of the future, whose successful deployment requires solving challenges from many domains. Model-based systems engineering (MBSE) is a key enabler for such complex systems of systems as can be seen by the increased number of related publications in key conferences and journals. This paper aims to characterize the state of the art of MBSE for the smart factory through a systematic mapping study on this topic. Adopting a detailed search strategy, 1466 papers were initially identified. Of these, 222 papers were selected and categorized using a particular classification scheme. Hence, we present the concerns addressed by the modeling community for Industry 4.0, how these are investigated, where these are published, and by whom. The resulting research landscape can help to understand, guide, and compare research in this field. In particular, this report identifies the Industry 4.0 challenges addressed by the modeling community, but also the challenges that seem to be less investigated.

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“…The authors select a panel of 176 related papers and identify a short list of most cited papers cf. Figure 2 (Berger, 2014;Brettel, Friederichsen, Keller, & Rosenberg, 2014;Hermann et al, 2016;Kagermann, Helbig, Hellinger, & Wahlster, 2013;Schuh et al, 2017;Vogel-Heuser & Hess, 2016). From an analysis of the positioning of those articles, a comprehensive list of prerequisites for Industry 4.0 compliant control systems is synthesized.…”

Section: Introductionmentioning

confidence: 99%

Industry 4.0: contributions of holonic manufacturing control architectures and future challenges

2020

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The flexibility claimed by the next generation production systems induces a deep modification of the behaviour and the core itself of the control systems. Over-connectivity and data management abilities targeted by Industry 4.0 paradigm enable the emergence of more flexible and reactive control systems, based on the cooperation of autonomous and connected entities in the decision-making process. From most relevant articles extracted from existing literature, a list of 10 key enablers for Industry 4.0 is first presented. During the last 20 years, the holonic paradigm has become a major paradigm of Intelligent Manufacturing Systems. After the presentation of the holonic paradigm and holon properties, this article highlights how historical and current holonic control architectures can partly fulfil I4.0 key enablers. The remaining unfulfilled key enablers are then the subject of an extensive discussion on the remaining research perspectives on holonic architectures needed to achieve a complete support of Industry4.0.

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Guest Editorial Industry 4.0–Prerequisites and Visions

Cited by 299 publications

References 6 publications

Deep digital maintenance

Deep digital maintenance

A Systematic Mapping Study on Modeling for Industry 4.0

Industry 4.0: contributions of holonic manufacturing control architectures and future challenges

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