Quantifying data for group technology with weighted fuzzy features
作者:
DAVID BEN-ARIEH,
EVANGELOS TRIANTAPHYLLOU,
期刊:
International Journal of Production Research
(Taylor Available online 1992)
卷期:
Volume 30,
issue 6
页码: 1285-1299
ISSN:0020-7543
年代: 1992
DOI:10.1080/00207549208942957
出版商: Taylor & Francis Group
数据来源: Taylor
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
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