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Simulation-Based Innovization Using Data Mining for Production Systems Analysis
University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.ORCID iD: 0000-0003-0111-1776
University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
2011 (English)In: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing / [ed] Lihui Wang, Amos H. C. Ng, Kalyanmoy Deb, Springer London, 2011, 401-429 p.Chapter in book (Refereed)
Abstract [en]

This chapter introduces a novel methodology for the analysis and optimization of production systems. The methodology is based on the innovization procedure, originally introduced for unveiling new and innovative design principles in engineering design problems. Although the innovization method is based on multi-objective optimization and post-optimality analyses of optimised solutions, it stretches the scope beyond an optimization task and attempts to discover new design/operational rules/principles relating to decision variables and objectives, so that a deeper understanding of the problem can be obtained. By integrating the concept of innovization with discrete-event simulation and data mining techniques, a new set of powerful tools can be developed for general systems analysis, particularly suitable for production systems. The uniqueness of the integrated approach proposed in this chapter lies on applying data mining to the data sets generated from simulation-based multi-objective optimization, in order to automatically or semi-automatically discover and interpret the hidden relationships and patterns for optimal production systems design/reconfiguration.

Place, publisher, year, edition, pages
Springer London, 2011. 401-429 p.
National Category
Engineering and Technology
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-5839DOI: 10.1007/978-0-85729-652-8_15ISBN: 978-0-85729-617-7 ISBN: 978-0-85729-652-8 OAI: oai:DiVA.org:his-5839DiVA: diva2:524779
Available from: 2012-05-03 Created: 2012-05-03 Last updated: 2015-12-18Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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