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dc.contributor.authorGhosh, Tamal
dc.contributor.authorDan, Pranab
dc.date.accessioned2019-01-21T13:48:21Z
dc.date.available2019-01-21T13:48:21Z
dc.date.created2018-12-17T11:39:53Z
dc.date.issued2012
dc.identifier.citationInternational Journal of Services and Operations Management. 2012, 13 (4), 441-456.nb_NO
dc.identifier.issn1744-2389
dc.identifier.urihttp://hdl.handle.net/11250/2581589
dc.description.abstractAbstract: Component/part family identification is an NP class problem in the extent of group technology (GT). In preceding literature it has been evidenced that part family identification techniques are ordinarily grounded on production flow analysis which typically studies operational requirements, sequences and time required. Recently, various soft-computing-based techniques are heavily attempted to address such problems. However in designing of parts, process planning, these methods are not convenient. To accomplish such issues coding and classification-based techniques are believed to be extremely proficient. This article portrays a minimal and competent nature inspired heuristic approach based on particle swarm optimisation (PSO) to acquire effective component/part families; exploiting part coding scheme and the technique is verified on top of test data as well as industrial data. The simulation outcomes are assessed with the results achieved using simple heuristic clustering method. The experimental results recommend that the proposed method is more effective in terms of computational efficiency and has outperformed the heuristic technique with enhanced solution quality.nb_NO
dc.language.isoengnb_NO
dc.publisherIndersciencenb_NO
dc.titleParticle swarm optimisation in development of component families using classification and coding system: a case study in an Indian manufacturing firmnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber441-456nb_NO
dc.source.volume13nb_NO
dc.source.journalInternational Journal of Services and Operations Managementnb_NO
dc.source.issue4nb_NO
dc.identifier.doi10.1504/IJSOM.2012.050140
dc.identifier.cristin1644049
dc.description.localcode© 2012. This is the authors' accepted and refereed manuscript to the article. The final authenticated version is available online at: https://dx.doi.org/10.1504/IJSOM.2012.050140nb_NO
cristin.unitcode194,64,94,0
cristin.unitnameInstitutt for vareproduksjon og byggteknikk
cristin.ispublishedtrue
cristin.fulltextpreprint


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