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Conference Paper: Two-stage product platform development for mass customization

TitleTwo-stage product platform development for mass customization
Authors
KeywordsMass customization
Product platform
Genetic Algorithm
Graph Theory
Issue Date2010
PublisherSpringer-Verlag.
Citation
The 6th International Conference On Digital Enterprise Technology (DET 2009), Hong Kong, 14-16 December. In Proceedings of DET'09, 2010, v. 66, p. 259-275 How to Cite?
AbstractNew products often evolve from past and existing products. This evolution largely defines the enterprise competitiveness in terms of the speed, quality and cost. Those design features that have proven successful or “fit” will survive and therefore be inherited by the new products, forming what is usually called a product “platform” and in turn providing a basis for mass customization (MC). This approach to new product development is generally termed as “Platform Product Development”. Whether or not an enterprise is able to capitalize on the concept of product platforms is vital to its business survival and growth. Whilst the approach has been widely appreciated and practiced with success in several industrial sectors, its industrial practice has remained as an art, heavily dependent on the experience and skills of individual designers and managers. Researchers and management consultants have been working on platform leveraging strategies at the strategic level, and guidelines for better structuring the approach to facilitate its adoption and implementation. This research project recognizes an equal need for scientific decision supports at the tactical level for design practitioners and managers to address fundamental questions such as (A) how a platform should be established for a family of products in a given industrial and market context, and (B) how a product development team chooses and then customizes the most appropriate product platform to meet the customer requirements from a specific market segment with particular manufacturing resources and supply bases. This paper is to describe a scientific and effective decision - Genetic Algorithm to assist product development practitioners and managers with major decision activities in the process of platform product development under several focus areas.
Persistent Identifierhttp://hdl.handle.net/10722/126224
ISSN

 

DC FieldValueLanguage
dc.contributor.authorQu, Ten_HK
dc.contributor.authorBin, Sen_HK
dc.contributor.authorHuang, GQen_HK
dc.contributor.authorYang, HDen_HK
dc.date.accessioned2010-10-31T12:16:36Z-
dc.date.available2010-10-31T12:16:36Z-
dc.date.issued2010en_HK
dc.identifier.citationThe 6th International Conference On Digital Enterprise Technology (DET 2009), Hong Kong, 14-16 December. In Proceedings of DET'09, 2010, v. 66, p. 259-275en_HK
dc.identifier.issn1867-5662-
dc.identifier.urihttp://hdl.handle.net/10722/126224-
dc.description.abstractNew products often evolve from past and existing products. This evolution largely defines the enterprise competitiveness in terms of the speed, quality and cost. Those design features that have proven successful or “fit” will survive and therefore be inherited by the new products, forming what is usually called a product “platform” and in turn providing a basis for mass customization (MC). This approach to new product development is generally termed as “Platform Product Development”. Whether or not an enterprise is able to capitalize on the concept of product platforms is vital to its business survival and growth. Whilst the approach has been widely appreciated and practiced with success in several industrial sectors, its industrial practice has remained as an art, heavily dependent on the experience and skills of individual designers and managers. Researchers and management consultants have been working on platform leveraging strategies at the strategic level, and guidelines for better structuring the approach to facilitate its adoption and implementation. This research project recognizes an equal need for scientific decision supports at the tactical level for design practitioners and managers to address fundamental questions such as (A) how a platform should be established for a family of products in a given industrial and market context, and (B) how a product development team chooses and then customizes the most appropriate product platform to meet the customer requirements from a specific market segment with particular manufacturing resources and supply bases. This paper is to describe a scientific and effective decision - Genetic Algorithm to assist product development practitioners and managers with major decision activities in the process of platform product development under several focus areas.-
dc.languageengen_HK
dc.publisherSpringer-Verlag.-
dc.relation.ispartofProceedings of the 6th CIRP-Sponsored International Conference on Digital Enterprise Technology, Advances in Intelligent and Soft Computing-
dc.subjectMass customization-
dc.subjectProduct platform-
dc.subjectGenetic Algorithm-
dc.subjectGraph Theory-
dc.titleTwo-stage product platform development for mass customizationen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailQu, T: quting@hku.hken_HK
dc.identifier.emailBin, S: bins@graduate.hku.hken_HK
dc.identifier.emailHuang, GQ: gqhuang@hkucc.hku.hken_HK
dc.identifier.emailYang, HD: yanghd@yeah.neten_HK
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1007/978-3-642-10430-5_20-
dc.identifier.scopuseid_2-s2.0-84903832323-
dc.identifier.hkuros175694en_HK
dc.identifier.volume66-
dc.identifier.spage259-
dc.identifier.epage275-
dc.identifier.eissn1867-5670-
dc.description.otherThe 6th International Conference On Digital Enterprise Technology (DET 2009), Hong Kong, 14-16 December. In Proceedings of DET'09, 2010, v. 66, p. 259-275-
dc.identifier.issnl1867-5662-

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