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K. Meixner, A. Lüder, J. Herzog, H. Röpke, S. Biffl:
"Modeling Expert Knowledge for Optimal CPPS Resource Selection for a Product Portfolio";
Vortrag: 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Vienna, Austria; 08.09.2020 - 11.09.2020; in: "Proceedings of the 25th International Conference on Emerging Technologies and Factory Automation (ETFA)", IEEE, (2020), S. 1687 - 1694.

Optimal selection of resources for a Cyber-Physical
Production System (CPPS) has a strong potential to reduce
the cost of producing product families. Unfortunately, engineers
rarely have specific methods and tools to represent their expert
knowledge for applying mathematical optimization approaches.
Representing this knowledge requires capabilities to model the
dependencies between products, production processes, resources,
skills, and their variability. In this paper, we provide these
capabilities and focus on improving CPPS resource selection by
defining aggregated requirements of a set of similar processes
for resources. We illustrate the industrial use case Car Body
with Screwed-on Parts on defining requirements for resource
candidates suitable for a set of screwing process variants.
We introduce the Product-Process-Resource-Skill & Variability
(PPRS+V) method for consistently designing aggregated ProductProcess-Resource (PPR) skills required for optimal CPPS resource selection as foundation for engineering support. We
introduce the Skill Aggregation algorithm to efficiently aggregate
the skills for a process step required to produce a product family.
In an initial feasibility study, domain experts found the PPRS+V
method and the Skill Aggregation algorithm usable and useful.

CPPS engineering, CPPS optimization, modelbased engineering, PPRS modeling, variability modeling

http://dx.doi.org/10.1109/ETFA46521.2020.9212067