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Article: Genetic algorithm-based optimisation method for product family design with multi-level commonality

TitleGenetic algorithm-based optimisation method for product family design with multi-level commonality
Authors
KeywordsGenetic algorithm
Mass customisation
Multi-level commonality
Non-dominated sorting genetic algorithm II
Product family
Issue Date2008
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/09544828.asp
Citation
Journal Of Engineering Design, 2008, v. 19 n. 5, p. 401-416 How to Cite?
AbstractAn increasing number of companies design a family of product variants simultaneously in order to introduce adequate product variety in the competitive market in a cost-effective way while shortening product lead-times, instead of designing one product at a time. The key to using this approach successfully is to achieve the right trade-off between product family commonality and performance of individual product variants. This paper considers multi-level commonality in product family design in the sense that the feature or component can be common only among some product variants. This differs from the two extremes of being totally common throughout the family or being completely different from one product variant to another. A product family design model is proposed as a multi-objective optimisation. A commonality index is introduced to evaluate the family commonality in the presence of multiple levels. A multi-objective genetic algorithm is developed for simultaneous design of a family of product variants. Optimal decisions include which design variables should be common among which product variants. Computational experiments are conducted using the design of a family of welded beams to demonstrate the effectiveness of the product family design method proposed in this paper.
Persistent Identifierhttp://hdl.handle.net/10722/58864
ISSN
2015 Impact Factor: 1.946
2015 SCImago Journal Rankings: 0.852
ISI Accession Number ID
Funding AgencyGrant Number
NSFC70629002
HKU CRCG
Funding Information:

Financial supports from NSFC (#70629002) and HKU CRCG are gratefully acknowledged for this research. Authors are grateful to referees and editors for their constructive suggestions for improving this paper.

References

 

DC FieldValueLanguage
dc.contributor.authorHuang, GQen_HK
dc.contributor.authorLi, Len_HK
dc.contributor.authorSchulze, Len_HK
dc.date.accessioned2010-05-31T03:38:23Z-
dc.date.available2010-05-31T03:38:23Z-
dc.date.issued2008en_HK
dc.identifier.citationJournal Of Engineering Design, 2008, v. 19 n. 5, p. 401-416en_HK
dc.identifier.issn0954-4828en_HK
dc.identifier.urihttp://hdl.handle.net/10722/58864-
dc.description.abstractAn increasing number of companies design a family of product variants simultaneously in order to introduce adequate product variety in the competitive market in a cost-effective way while shortening product lead-times, instead of designing one product at a time. The key to using this approach successfully is to achieve the right trade-off between product family commonality and performance of individual product variants. This paper considers multi-level commonality in product family design in the sense that the feature or component can be common only among some product variants. This differs from the two extremes of being totally common throughout the family or being completely different from one product variant to another. A product family design model is proposed as a multi-objective optimisation. A commonality index is introduced to evaluate the family commonality in the presence of multiple levels. A multi-objective genetic algorithm is developed for simultaneous design of a family of product variants. Optimal decisions include which design variables should be common among which product variants. Computational experiments are conducted using the design of a family of welded beams to demonstrate the effectiveness of the product family design method proposed in this paper.en_HK
dc.languageengen_HK
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/09544828.aspen_HK
dc.relation.ispartofJournal of Engineering Designen_HK
dc.subjectGenetic algorithmen_HK
dc.subjectMass customisationen_HK
dc.subjectMulti-level commonalityen_HK
dc.subjectNon-dominated sorting genetic algorithm IIen_HK
dc.subjectProduct familyen_HK
dc.titleGenetic algorithm-based optimisation method for product family design with multi-level commonalityen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0954-4828&volume=19&issue=5&spage=401&epage=416&date=2008&atitle=Genetic+algorithm-based+optimisation+method+for+product+family+design+with+multi-level+commonality+en_HK
dc.identifier.emailHuang, GQ:gqhuang@hkucc.hku.hken_HK
dc.identifier.authorityHuang, GQ=rp00118en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/09544820701642063en_HK
dc.identifier.scopuseid_2-s2.0-51849092274en_HK
dc.identifier.hkuros149660en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-51849092274&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume19en_HK
dc.identifier.issue5en_HK
dc.identifier.spage401en_HK
dc.identifier.epage416en_HK
dc.identifier.isiWOS:000259239600001-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridHuang, GQ=7403425048en_HK
dc.identifier.scopusauthoridLi, L=36985950400en_HK
dc.identifier.scopusauthoridSchulze, L=22235712200en_HK
dc.identifier.citeulike3344299-

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