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A methodology for microstructure-based structural optimization of cast and injection moulded parts using knowledge-based design automation
Department of Materials and Manufacturing – Casting, Jönköping University, School of Engineering, Jönköping, Sweden.
Department of Product Development, Jönköping University, School of Engineering, Jönköping, Sweden.
Department of Product Development, Jönköping University, School of Engineering, Jönköping, Sweden.
University of Skövde, School of Engineering Science.ORCID iD: 0000-0001-7534-0382
2017 (English)In: Advances in Engineering Software, ISSN 0965-9978, E-ISSN 1873-5339, Vol. 109, 44-52 p.Article in journal (Refereed) Published
Abstract [en]

The local material behaviour of cast metal and injection moulded parts is highly related to the geometrical design of the part as well as to a large number of process parameters. In order to use structural optimization methods to find the geometry that gives the best possible performance, both the geometry and the effect of the production process on the local material behaviour thus has to be considered. In this work, a multidisciplinary methodology to consider local microstructure-based material behaviour in optimizations of the design of engineering structures is presented. By adopting a knowledge based industrial product realisation perspective combined with a previously presented simulation strategy for microstructure-based material behaviour in Finite Element Analyses (FEA), the methodology integrates Computer Aided Design (CAD), casting and injection moulding simulations, FEA, design automation and a multi-objective optimization scheme into a novel structural optimization method for cast metal and injection moulded polymeric parts. The different concepts and modules in the methodology are described, their implementation into a prototype software is outlined, and the application and relevance of the methodology is discussed. 

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 109, 44-52 p.
Keyword [en]
Component casting, Injection moulding, Design automation, Knowledge based engineering, Finite element analysis, Multi-objective optimization
Identifiers
URN: urn:nbn:se:his:diva-13576DOI: 10.1016/j.advengsoft.2017.03.003ISI: 000400217700004ScopusID: 2-s2.0-85016937770OAI: oai:DiVA.org:his-13576DiVA: diva2:1097945
Available from: 2017-05-23 Created: 2017-05-23 Last updated: 2017-05-30

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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  • asciidoc
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