Product Variety Modeling Based on Formal Concept Analysis

Title & Authors
Product Variety Modeling Based on Formal Concept Analysis
Kim, Tai-Oun;

Abstract
Increasing product variety based on product family and product platform provides a company with a competitive advantage over its competitors. As products become more complex, short-life cycled and customized, the design efforts require more knowledge-intensive, collaborative and coordinating efforts for information sharing. By sharing knowledge, information, component and process across different families of products, the product realization process will be more efficient, cost-effective and quick-responsive. Formal Concept Analysis (FCA) is used for analyzing data and forming semantic structures that are formal abstractions of concepts of human thoughts. A Web Ontology Language (OWL) is designed for applications that need to process the content of information instead of simply presenting information to humans. OWL also captures the evolution of different components of the product family. The purpose of this paper is to develop product variety modeling to increase the usefulness of common platform. In constructing and analyzing product ontology, FCA is adopted for conceptual knowledge processing. For the selected product family, product variety Ontology is constructed and implemented using prot$\small{\$g$\small{\$-2000.
Keywords
Product Variety;Product Family;OWL;Semantic Web;Ontology;Formal Concept Analysis;
Language
English
Cited by
1.
Analytic Network Process에 기초한 제품가족 디자인,김태운;

지능정보연구 , 2011. vol.17. 4, pp.1-17
References
1.
Brown, D. (2003), Functional, Behavioral and Structural Features, Proceedings of the DETC 2003 ASME Design Engineering Technical Conferences, DETC20 03/DTM-48684, Chicago, Illinois.

2.
Eijck, J. and Zwarts, J. (2004), Formal Concept Analysis and Prototypes, working paper.

3.
Ishii, K., Ichimura, T., and Hiraki, S. (2003), Analysis of Information Behavior in the Determination of Product Specifications Based on a Conjoint Measurement Approach and Fusion Model, Industrial Engineering and Management Systems, 2(1), 55-62.

4.
Kim, K. and Kim, D. (2008), Research Issues in Robust QFD, Industrial Engineering and Management Systems, 7(2), 93-100.

5.
Koga, T. and Aoyama, K. (2004), Product Behavior and Topological Structure Design System by Step-by-Step Decomposition, Proceedings of DETC'04 (Design Engineering Technical Conferences), DECT2004-57513, September 28-October 2, Salt Lake City, Utah.

6.
Kota, K., Sethuraman, K., and Miller, R. (2000), A Metric for Evaluating Design Commonality in Product Families, Journal of Mechanical Design, 122, 403-410.

7.
Martin, M. V. and Ishii, K. (2003), Design for Variety: Developing Standardized and Modularized Product Platform Architectures, Research in Engineering Design, 13, 213-235.

8.
Min, S., Matsuoka, S., and Muraki, M. (2004), Priority Assignment Procedure in Multi-Product Disassembly, Industrial Engineering and Management Systems, 3(1), 12-21.

9.
Nanda, J., Thevenot, H., Simpson, T., and Kumara, S. (2004), Exploring Semantic Web Technologies for Product Family Modeling, Proceedings of DETC '04 (Design Engineering Technical Conferences), DE CT2004-57683, September 28-October 2, Salt Lake City, Utah.

10.
Priss, U. (2005), Formal Concept Analysis in Information Science, Annual Review of Information Science and Technology, Edited by Blaise Cronin, 1-17.

11.
Simpson, T. W., Maier, R. A., and Mistree, F. (2001), Product Platform Design: Method and Application, Research in Engineering Design, 13, 2-22.

12.
Ulrich, K. T. and Eppinger, S. D. (2003), Product Design and Development, Third edition, McGraw-Hill, Inc, Singapore.