Data-mining approach to support layout configuration decision-making in Evolvable Production Systems

Pedro Neves, Luis Ribeiro, Joao Dias-Ferreira, Antonio Maffei, Mauro Onori, Jose Barata

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2014)
Place of PublicationNew York
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3649-3656
Number of pages8
ISBN (Electronic)978-1-4799-3840-7
ISBN (Print)978-1-4799-3841-4
DOIs
Publication statusPublished - 2014
EventIEEE International Conference on Systems, Man, and Cybernetics (SMC) - San Diego, Canada
Duration: 5 Oct 20148 Oct 2014

Publication series

NameIEEE International Conference on Systems Man and Cybernetics Conference Proceedings
PublisherIEEE
Volume2014-January
ISSN (Print)1062-922X

Conference

ConferenceIEEE International Conference on Systems, Man, and Cybernetics (SMC)
CountryCanada
CitySan Diego
Period5/10/148/10/14

Keywords

  • Self-Organising Mechatronic Systems
  • Assembly Systems design
  • Simulation Tools
  • Multi-agent Systems
  • Data-Mining

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