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A methodology for microstructure-based structural optimization of cast and injection moulded parts using knowledge-based design automation
Högskolan i Jönköping, Tekniska Högskolan, JTH, Material och tillverkning. Högskolan i Jönköping, Tekniska Högskolan, JTH. Forskningsmiljö Material och tillverkning – Gjutning.ORCID-id: 0000-0003-2671-9825
Högskolan i Jönköping, Tekniska Högskolan, JTH, Produktutveckling. Högskolan i Jönköping, Tekniska Högskolan, JTH. Forskningsmiljö Produktutveckling - Simulering och optimering.ORCID-id: 0000-0003-0899-8939
Högskolan i Jönköping, Tekniska Högskolan, JTH, Produktutveckling. Högskolan i Jönköping, Tekniska Högskolan, JTH. Forskningsmiljö Produktutveckling - Datorstödd konstruktion.ORCID-id: 0000-0003-1162-724X
University of Skövde, Sweden.
2017 (engelsk)Inngår i: Advances in Engineering Software, ISSN 0965-9978, E-ISSN 1873-5339, Vol. 109, 44-52 s.Artikkel i tidsskrift (Fagfellevurdert) 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.

sted, utgiver, år, opplag, sider
Elsevier, 2017. Vol. 109, 44-52 s.
Emneord [en]
Component casting, Injection moulding, Design automation, Knowledge based engineering, Finite element analysis, Multi-objective optimization
HSV kategori
Identifikatorer
URN: urn:nbn:se:hj:diva-35390DOI: 10.1016/j.advengsoft.2017.03.003ISI: 000400217700004Scopus ID: 2-s2.0-85016937770OAI: oai:DiVA.org:hj-35390DiVA: diva2:1089564
Tilgjengelig fra: 2017-04-20 Laget: 2017-04-20 Sist oppdatert: 2017-05-18bibliografisk kontrollert

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