QUANTIFYING DATA FOR GROUP TECHNOLOGY WITH WEIGHTED FUZZY FEATURES

被引：30

作者：

BENARIEH, D

TRIANTAPHYLLOU, E

机构：

[1] Department of Industrial Engineering, Durland Hall Kansas State University, Manhattan, KS

来源：

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH | 1992年 / 30卷 / 06期

关键词：

D O I：

10.1080/00207549208942957

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The high potential of using group technology in manufacturing has attracted the interest of both practitioners and researchers. Group technology is based on clustering parts which have similar features. Very often it is very hard to quantify successfully data regarding these features. This is because in many real applications features are fuzzy. This paper identifies two types of fuzzy features: qualitative features, and quantitative ones with subjective meaning. The paper presents a methodology for quantifying the data that refer to the fuzzy features. The proposed methodology deals with crisp and fuzzy data in a unified manner. Finally, some clustering approaches which process the quantified features are also discussed.

引用

页码：1285 / 1299

页数：15

共 24 条

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