Data-mining approach to support layout configuration decision-making in Evolvable Production Systems
2014 (English)In: Proceedings 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC) October 5-8, 2014, San Diego, CA, USA, IEEE conference proceedings, 2014, 3649-3656 p.Conference paper (Refereed)
Computational and communication capabilities are increasingly being used in all devices. In the production context this leads to the generation of massive amounts of data that are rarely proficuously used. More particularly the application of data-mining techniques to infer knowledge from systems’ operation to improve its design decisions remains fairly unexplored. This article presents an approach to extract system design and configuration rules from Evolvable Production Systems. Furthermore it provides the empirical results from two test-cases that support the hypothesis that a simulation-data-mining approach can help reducing the complexity of the work carried by system designers and production managers.
Place, publisher, year, edition, pages
IEEE conference proceedings, 2014. 3649-3656 p.
, IEEE International Conference on Systems Man and Cybernetics Conference Proceedings, ISSN 1062-922X
Self-Organising Mechatronic Systems; Assembly Systems design; Simulation Tools; Multi-agent Systems; Data-Mining
Other Electrical Engineering, Electronic Engineering, Information Engineering Production Engineering, Human Work Science and Ergonomics
IdentifiersURN: urn:nbn:se:liu:diva-109307DOI: 10.1109/SMC.2014.6974497ISI: 000370963703131ISBN: 978-1-4799-3840-7OAI: oai:DiVA.org:liu-109307DiVA: diva2:737065
IEEE International Conference on Systems, Man and Cybernetics (IEE SMC 2014 ), 5-8 October 2014, San Diego, CA, USA