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Utilizing Software Design Patterns in Product-Driven Manufacturing System: A Case Study

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 853))

Abstract

This paper presents the development of a flexible product-driven manufacturing exemplified in a case study. The case study is based on Festo EnAS (“Energieautarke Aktoren und Sensoren” or “energy efficient actuators and sensors” in English) platform, enhanced with a mobile robot for logistics and a camera for automated visual-based product inspection. IEC 61499-based and wireless-capable embedded controllers are used to enable decentralized control architecture. In this case study, a software design pattern is considered to enable easier development of modular production systems with physically reconfigurable layout during the production process. This paper applies the software design pattern into production systems where product-driven approach is adopted, i.e. the overall production process is determined based on the product specifications/requirements from the customer.

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Acknowledgment

The authors would like to thank Mr. Vesa Korhonen, the EEK department technician who have helped us a lot in technical and logistical support. The authors would like to also acknowledge our industrial partners who have provided their support on this project, to name a few, NxtControl that has provided NxtStudio software and to Festo that has provided a space to exhibit this project during the ScanAutomatic 2018 event in Gothenburg, Sweden. The project was partially funded by the European project DAEDALUS (H2020 Grant Agreement n\(^\circ \): 723248) and the Aalto Factory of the Future initiative from School of Electrical Engineering of Aalto University.

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Correspondence to Dmitrii Drozdov .

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Drozdov, D. et al. (2020). Utilizing Software Design Patterns in Product-Driven Manufacturing System: A Case Study. In: Borangiu, T., Trentesaux, D., Leitão, P., Giret Boggino, A., Botti, V. (eds) Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future. SOHOMA 2019. Studies in Computational Intelligence, vol 853. Springer, Cham. https://doi.org/10.1007/978-3-030-27477-1_23

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