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Variability Modeling of Products, Processes, and Resources in Cyber-Physical Production Systems Engineering

Meixner, Kristof; Feichtinger, Kevin ORCID iD icon 1; Fadhlillah, Hafiyyan Sayyid; Greiner, Sandra; Marcher, Hannes; Rabiser, Rick; Biffl, Stefan
1 Institut für Informationssicherheit und Verlässlichkeit (KASTEL), Karlsruher Institut für Technologie (KIT)

Abstract:

Cyber-Physical Production Systems (CPPSs), such as automated car manufacturing plants, execute a configurable sequence of production steps to manufacture products from a product portfolio. In CPPS engineering, domain experts start with manually determining feasible production step sequences and resources based on implicit knowledge. This process is hard to reproduce and highly inefficient. In this paper, we present the Extended Iterative Process Sequence Exploration (eIPSE) approach to derive variability models for products, processes, and resources from a domain-specific description. To automate the integrated exploration and configuration process for a CPPS, we provide a toolchain which automatically reduces the configuration space and allows to generate CPPS artifacts, such as control code for resources. We evaluate the approach with four real-world use cases, including the generation of control code artifacts, and an observational user study to collect feedback from engineers with different backgrounds. The results confirm the usefulness of the eIPSE approach and accompanying prototype to straightforwardly configure a desired CPPS.


Postprint §
DOI: 10.5445/IR/1000168801
Veröffentlicht am 26.02.2024
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Informationssicherheit und Verlässlichkeit (KASTEL)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2024
Sprache Englisch
Identifikator ISSN: 0164-1212
KITopen-ID: 1000168801
Erschienen in Journal of Systems and Software
Verlag Elsevier
Seiten Article no: 112007
Projektinformation SFB 1608/1 (DFG, DFG KOORD, SFB 1608)
Vorab online veröffentlicht am 24.02.2024
Schlagwörter Variability Modeling, Feature Modeling, Decision Modeling, Production Process Variability, Cyber-Physical Production System
Nachgewiesen in Scopus
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