DSpace logo

Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/11715
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSangwan, Kuldip Singh-
dc.date.accessioned2023-08-28T09:56:44Z-
dc.date.available2023-08-28T09:56:44Z-
dc.date.issued2008-02-
dc.identifier.urihttps://www.tandfonline.com/doi/abs/10.1080/09537280410001697729-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/11715-
dc.description.abstractMost of the techniques related to part family formation require precise numerical data for part's features. However, in many situations, the parts features are too ill-defined and are too susceptible to analysis by traditional discrete methods. Fuzzy set theory allows the parts to belong to different groups with different memberships. Moreover, different attributes may not have equal importance. The AHP (analytical hierarchy process) model gives the weightage for different attributes and also checks the consistency of the judgements. This paper suggests two models for part family formation using fuzzy mathematics and the AHP model. One model is based on fuzzy logic and AHP and the second model uses fuzzy equivalence ratios and AHP. Models can be integrated with the existing coding systems used by organizations. Both models are validated using problems from literature.en_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subjectMechanical Engineeringen_US
dc.subjectGTen_US
dc.subjectCMSen_US
dc.subjectPart familyen_US
dc.subjectFuzzy AHPen_US
dc.titleFuzzy part family formation for cellular manufacturing systemsen_US
dc.typeArticleen_US
Appears in Collections:Department of Mechanical engineering

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.