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SQUADfps: Integrated Model-Based Machine Safety and Product Quality for Flexible Production Systems

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Model-Based Safety and Assessment (IMBSA 2019)

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Abstract

Growing individualization of products up to lot-size-1 and high volatility of product mixes lead to new challenges in the manufacturing domain, including the need for frequent reconfiguration of the system and reacting to changing orders. Thus, apart from functional aspects, safety aspects of the production system as well as product quality assurance aspects must be addressed for flexible and reconfigurable manufacturing systems at runtime. To cope with the mentioned challenges, we present an integrated model-based approach SQUADfps (machine Safety and product QUAlity for flexible proDuction systems) to support the automatic conduct of the risk assessment of flexible production scenarios in terms of safety as well as the process-FMEA to ensure that the requirements w.r.t. the quality of the production process and the resulting product are met. Our approach is based on a meta-model which captures all information needed to conduct both risk assessment and process-FMEA dynamically during the runtime, and thus enables flexible manufacturing scenarios with frequent changes of the production system and orders up to a lot-size of one while guaranteeing safety and product quality requirements. The automatically generated results will assist human in making further decisions. To demonstrate the feasibility of our approach, we apply it to a case study.

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Acknowledgement

The work leading to this paper was funded by the German Federal Ministry of Education and Research under grant number 01IS16043Q and 01IS16043O (CrESt).

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Correspondence to Chee Hung Koo .

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Koo, C.H., Rothbauer, S., Vorderer, M., Höfig, K., Zeller, M. (2019). SQUADfps: Integrated Model-Based Machine Safety and Product Quality for Flexible Production Systems. In: Papadopoulos, Y., Aslansefat, K., Katsaros, P., Bozzano, M. (eds) Model-Based Safety and Assessment. IMBSA 2019. Lecture Notes in Computer Science(), vol 11842. Springer, Cham. https://doi.org/10.1007/978-3-030-32872-6_15

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  • DOI: https://doi.org/10.1007/978-3-030-32872-6_15

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  • Online ISBN: 978-3-030-32872-6

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