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A novel I4.0-enabled engineering method and its evaluation

  • Frederick PrinzEmail author
  • Michael Schoeffler
  • Armin Lechler
  • Alexander Verl
ORIGINAL ARTICLE
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Abstract

Recent trends show that products are becoming more complex and multi-variant. Therefore, future production systems need to become more advanced in terms of reconfigurability, flexibility, and transformability. To achieve these advancements, future systems must be highly changeable and support plug-and-produce approaches. The majority of today’s engineering methods focus on static workflows based on predefined assets and setups. As a consequence, changes in the production system come with high costs, especially during production process execution. Therefore, new engineering methods are required which are explicitly designed for highly changeable production systems. To contribute towards fully changeable production systems, an I4.0 framework is proposed that covers the entire engineering process. The focus is set on presenting a graphical I4.0-enabled engineering method that enables dynamic workflows with varying assets and setups. Moreover, in order to evaluate the method, a user study was conducted, in which participants were asked to solve multiple engineering tasks by utilizing the presented I4.0-enabled method as well as a conventional approach. The results indicated that the proposed I4.0-enabled engineering method significantly outperformed the conventional method in terms of required engineering times and subjective ratings.

Keywords

Industry 4.0 Industrial internet of things Changeability Framework Workflow engineering Business process modeling and notation User study 
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Notes

Acknowledgements

We would like to thank all participants of the user study for spending their time and valuable feedback. Moreover, we want to thank our colleagues, from the “Advanced Production and Automation” department of the Corporate Research division of Robert Bosch GmbH, who were involved in the development of the presented work.

Funding information

This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 680759.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  • Frederick Prinz
    • 1
    Email author
  • Michael Schoeffler
    • 1
  • Armin Lechler
    • 2
  • Alexander Verl
    • 2
  1. 1.Corporate Sector Research and Advance EngineeringRobert Bosch GmbHRenningenGermany
  2. 2.Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW)University of StuttgartStuttgartGermany

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