Towards a knowledge support system for product family design

Seung Ki Moon; Xiaomeng Chang; Janis Terpenny; Timothy W. Simpson; Soundar R.T. Kumara

doi:10.1142/9789814280280_0016

Towards a knowledge support system for product family design

Seung Ki Moon, Xiaomeng Chang, Janis Terpenny, Timothy W. Simpson, Soundar R.T. Kumara

Research output: Chapter in Book/Report/Conference proceeding › Chapter

1 Scopus citations

Abstract

This chapter describes research toward creating a knowledge support system (KSS) that consists of knowledge representation, knowledge discovery, and recommendation for product family design. For the proposed KSS, we use an ontology to represent products as functional-based hierarchical structures and describe cost information related to product design. Fuzzy clustering is employed to partition product functions into subsets for identifying a platform and modules in a given product family. Rules related to design knowledge among products are developed using association rule mining. A reasoning tool is used to inference knowledge represented by an ontology and obtain design solutions. We present a prototype system to demonstrate the KSS using a case study involving a family of power tools.

Original language	English (US)
Title of host publication	Handbook of Research in Mass Customization and Personalization
Publisher	World Scientific Publishing Co.
Pages	297-318
Number of pages	22
ISBN (Electronic)	9789814280280
ISBN (Print)	9789814280259
DOIs	https://doi.org/10.1142/9789814280280_0016
State	Published - Jan 1 2009

All Science Journal Classification (ASJC) codes

General Engineering
General Economics, Econometrics and Finance
General Business, Management and Accounting

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10.1142/9789814280280_0016

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AU - Chang, Xiaomeng

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AU - Simpson, Timothy W.

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AB - This chapter describes research toward creating a knowledge support system (KSS) that consists of knowledge representation, knowledge discovery, and recommendation for product family design. For the proposed KSS, we use an ontology to represent products as functional-based hierarchical structures and describe cost information related to product design. Fuzzy clustering is employed to partition product functions into subsets for identifying a platform and modules in a given product family. Rules related to design knowledge among products are developed using association rule mining. A reasoning tool is used to inference knowledge represented by an ontology and obtain design solutions. We present a prototype system to demonstrate the KSS using a case study involving a family of power tools.

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ER -

Towards a knowledge support system for product family design

Abstract

All Science Journal Classification (ASJC) codes

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