Biffl, S., Meixner, K., Hoffmann, D., Winkler, D., & Lüder, A. (2023). Towards Test-Driven Performance Validation of a Flexible Cyber-Physical Production System. In 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA) (pp. 1–4). IEEE. https://doi.org/10.1109/ETFA54631.2023.10275573
2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)
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Event date:
12-Sep-2023 - 15-Sep-2023
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Event place:
Sinaia, Romania
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Number of Pages:
4
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Publisher:
IEEE
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Peer reviewed:
Yes
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Keywords:
Behavior-Driven Development; Industry 4.0; PPR dependency management; Variability
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Abstract:
Fast changes in production require flexibility regarding products, production processes, and production resources (PPR), moving towards a flexible production system that consists of independent systems. However, production systems engineering traditionally considers mainly static systems and requires advanced capabilities to effectively and efficiently validate performance indicators specified in test scenarios for a flexible production system. For validating production process and system variants, this vision paper explores the Test-Driven Performance Validation (TPV) approach for knowledge representation of (1) a family of production variants (2) with test scenarios on production effects and conditions, and (3) a Production Asset Network that defines PPR configuration dependencies and production data sources as a foundation for calculating a production variant's performance. We conclude with a research agenda towards coordinating performance validation of flexible production with human and machine agents.
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Project title:
Verbesserung der Sicherheit von Informationsprozessen in Produktionssystemen: CDL SQI (Christian Doppler Forschungsgesells; Christian Doppler Forschungsgesells)
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Project (external):
Christian Doppler Forschungsgesellschaft
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Project ID:
CDL-SQI
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Research Areas:
Digital Transformation in Manufacturing: 40% Computer Engineering and Software-Intensive Systems: 30% Information Systems Engineering: 30%
