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Article: A RFID-based recursive process mining system for quality assurance in the garment industry

TitleA RFID-based recursive process mining system for quality assurance in the garment industry
Authors
Issue Date2014
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/00207543.asp
Citation
International Journal of Production Research, 2014, v. 52 n. 14, p. 4216-4238 How to Cite?
AbstractWith the increasing concern about product quality, attention has shifted to the monitoring of production processes to be assured of good quality. Achieving good quality is a challenging task in the garment industry due to the great complexity of garment products. This paper presents an intelligent system, using fuzzy association rule mining with a recursive process mining algorithm, to find the relationships between production process parameters and product quality. The goal is to derive a set of decision rules for fuzzy logic that will determine the quantitative values of the process parameters. Learnt process parameters used in production form new inputs of the initial step of the mining algorithm so that new sets of rules can be obtained recursively. Radio frequency identification technology is deployed to increase the efficiency of the system. With the recursive characteristics of the system, process parameters can be continually refined for the purpose of achieving quality assurance. A case study is described in which the system is applied in a garment manufacturing company. After a six-month pilot run of the system, the numbers of critical defects, major defects and minor defects were reduced by 7, 20 and 24%, respectively while production time and rework cost improved by 26 and 30%, respectively. Results demonstrate the practical viability of the system to provide decision support for garment manufacturers who may not be able to determine the appropriate process settings for achieving the desired product quality.
Persistent Identifierhttp://hdl.handle.net/10722/202820
ISSN
2015 Impact Factor: 1.693
2015 SCImago Journal Rankings: 1.445

 

DC FieldValueLanguage
dc.contributor.authorLee, CKH-
dc.contributor.authorHo, GTS-
dc.contributor.authorChoy, KL-
dc.contributor.authorPang, GKH-
dc.date.accessioned2014-09-19T10:08:02Z-
dc.date.available2014-09-19T10:08:02Z-
dc.date.issued2014-
dc.identifier.citationInternational Journal of Production Research, 2014, v. 52 n. 14, p. 4216-4238-
dc.identifier.issn0020-7543-
dc.identifier.urihttp://hdl.handle.net/10722/202820-
dc.description.abstractWith the increasing concern about product quality, attention has shifted to the monitoring of production processes to be assured of good quality. Achieving good quality is a challenging task in the garment industry due to the great complexity of garment products. This paper presents an intelligent system, using fuzzy association rule mining with a recursive process mining algorithm, to find the relationships between production process parameters and product quality. The goal is to derive a set of decision rules for fuzzy logic that will determine the quantitative values of the process parameters. Learnt process parameters used in production form new inputs of the initial step of the mining algorithm so that new sets of rules can be obtained recursively. Radio frequency identification technology is deployed to increase the efficiency of the system. With the recursive characteristics of the system, process parameters can be continually refined for the purpose of achieving quality assurance. A case study is described in which the system is applied in a garment manufacturing company. After a six-month pilot run of the system, the numbers of critical defects, major defects and minor defects were reduced by 7, 20 and 24%, respectively while production time and rework cost improved by 26 and 30%, respectively. Results demonstrate the practical viability of the system to provide decision support for garment manufacturers who may not be able to determine the appropriate process settings for achieving the desired product quality.-
dc.languageeng-
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/00207543.asp-
dc.relation.ispartofInternational Journal of Production Research-
dc.titleA RFID-based recursive process mining system for quality assurance in the garment industry-
dc.typeArticle-
dc.identifier.emailPang, GKH: gpang@eee.hku.hk-
dc.identifier.authorityPang, GKH=rp00162-
dc.identifier.doi10.1080/00207543.2013.869632-
dc.identifier.hkuros236050-
dc.identifier.volume52-
dc.identifier.issue14-
dc.identifier.spage4216-
dc.identifier.epage4238-
dc.publisher.placeUnited Kingdom-

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