TY - GEN
T1 - Product function - Component modeling using rough sets
AU - Miwa, Toshiharu
AU - Aoyama, Hideki
N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - The acceleration of the product development cycle continues to be a significant challenge for manufacturing firms around the world. The misunderstanding of important relationships between product functions and components leads the delay of product development. The present paper describes an identification method of the relationships between product functions and components at the early stage of product development. The proposed product function-component modeling method using rough sets theory extracts the characteristic relationships between product functions and components from a small amount of the qualitative and linguistically-expressed knowledge data. The advantage of using the rough sets is that the combination of necessary and possible sets (lower and upper approximations) represents the vague knowledge. The present paper describes an example of a conventional cutting process with 6 manufacturing parameters that this method contributes to the identification of cutting mechanism from a small amount of sampling data (7% of whole event) compared to the conventional statistical modeling method.
AB - The acceleration of the product development cycle continues to be a significant challenge for manufacturing firms around the world. The misunderstanding of important relationships between product functions and components leads the delay of product development. The present paper describes an identification method of the relationships between product functions and components at the early stage of product development. The proposed product function-component modeling method using rough sets theory extracts the characteristic relationships between product functions and components from a small amount of the qualitative and linguistically-expressed knowledge data. The advantage of using the rough sets is that the combination of necessary and possible sets (lower and upper approximations) represents the vague knowledge. The present paper describes an example of a conventional cutting process with 6 manufacturing parameters that this method contributes to the identification of cutting mechanism from a small amount of sampling data (7% of whole event) compared to the conventional statistical modeling method.
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M3 - Conference contribution
AN - SCOPUS:77953775790
SN - 9780791849057
T3 - Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference 2009, DETC2009
SP - 167
EP - 175
BT - Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference 2009, DETC2009
T2 - 2009 ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2009
Y2 - 30 August 2009 through 2 September 2009
ER -