DocumentCode
2632680
Title
Mining Rules from Stamping Die Designs
Author
Chi, Zhou ; Feng, Ruan
Author_Institution
Sch. of Mech. Eng., South China Univ. of Tech., Guangzhou
fYear
2008
fDate
18-20 June 2008
Firstpage
74
Lastpage
74
Abstract
To improve the performance of case based intelligent stamping die design systems, an approach based on rough set theory is proposed to mine rules from successful design cases. This approach is based on the mapping relation between stamping features and die designs. The mappings from the attributes of a feature to the related die design constitute the design knowledge. The method extracts the rules from the mapping relationship by applying fuzzy classification and computing attribute reduct. The mined rules can be integrated into traditional RBR systems to provide assistance for the design of a new part. Furthermore, these rules can also be used to speed up the case retrieval process of CBR systems by restricting the search space into a subgroup of cases.
Keywords
CAD; case-based reasoning; dies (machine tools); fuzzy set theory; pattern classification; production engineering computing; rough set theory; case based intelligent stamping die design systems; case based reasoning; fuzzy classification; rough set theory; rule based reasoning; Art; Artificial intelligence; Assembly; Design automation; Fuzzy sets; Indexing; Mechanical engineering; Process design; Set theory; Springs;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
Conference_Location
Dalian, Liaoning
Print_ISBN
978-0-7695-3161-8
Electronic_ISBN
978-0-7695-3161-8
Type
conf
DOI
10.1109/ICICIC.2008.361
Filename
4603263
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