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Process Model Automation For Industry 4.0: Challenges For Automated Model Generation Based On Laboratory Experiments

  • Marco Nardello
    ,
  • Charles Møller
    ,
  • John Gøtze
  • Aalborg University
Research Output:
Journal Article or Conference Article in Journal
Conference article
Peer-review

Open access

Publication Information

Output type

Research Output:
Journal Article or Conference Article in Journal
Conference article
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 201-215 (15 pages)

Journal (Volume, Issue Number)

CEUR Workshop Proceedings (Volume 2218)

Publication milestones

  • Published - 24/09/2018

Publication status

Published - 24/09/2018

ISSN

1613-0073

Publication IDs

  • Scopus: 85054313873

Abstract

Driven by technological advances and increasing customer demands, the complexity in manufacturing companies is rapidly growing. To manage this complexity numerous architecture standardization initiatives are emerging in the manufacturing industry, e.g. Production Platforms, Reference Architecture Model Industry 4.0 (RAMI4.0), Industrial Internet Reference Architecture (IIRA). Large manufacturing companies are changing their approach towards managing production and are adopting the concept of Production Platforms. Production Platforms can be understood as a set of subsystems and interfaces to create a common architecture to develop both products and production systems simultaneously. The development of the models required in these platforms is often performed manually and it is perceived as very time consuming. A discipline that can support the implementation of Production Platforms is Enterprise Architecture (EA). EA is a discipline that manages the organizing logic of the enterprise and it reflects the integration and standardization requirements of its operating model. Therefore modelling the products, production systems and process is in the scope of EA when applied to the manufacturing industry. In this paper, we develop a new automated EA modelling method relevant also for manufacturing. We tested it in an Industry 4.0 laboratory. This paper is a first step for creating automated EA modelling methods that are general-purpose and applicable in different contexts. With this goal in mind, we outline future research directions based on the limitations and challenges experienced during the laboratory experiments.

Publication metrics

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Captures
65
Citations
4

Access to documents

Final published version, 793.16 KB

Related Event

Title

17th International Conference Perspectives in Business Informatics Research (BIR 2018)

Event type

Conference

Date

24/09/2018 - 26/09/2018