An intelligent system for production resources planning in Hong Kong garment industry
Version 2 2024-06-05, 03:03Version 2 2024-06-05, 03:03
Version 1 2019-01-22, 11:07Version 1 2019-01-22, 11:07
conference contribution
posted on 2024-06-05, 03:03 authored by CKH Lee, KL Choy, Kris LawKris Law, GTS HoResources management has remarkable impacts on production operations in terms of both productivity and efficiency. Faced the challenges in the competitive market, garment manufacturers are always striking for shorter production cycles. Effective resources management is thus essential for the survivals of garment manufacturers. Currently, there is a lack of standardized approaches for effective production resources management in the garment manufacturing industry. This may lead to inefficiency in production performance. Problems aroused include inaccurate resources planning and allocation. This paper presents an intelligent resources management system, integrating both radio frequency identification (RFID) technology and fuzzy logic, specifically for the garment industry. A case study conducted in a Hong Kong garment manufacturing company, which is considered a good representation in the sector, is addressed. Results indicate that the proposed approach outperforms the conventional approaches with better decision making in resources planning. © 2012 IEEE.
History
Pagination
889-893Location
Hong KongPublisher DOI
Start date
2012-12-10End date
2012-12-13ISSN
2157-3611eISSN
2157-362XISBN-13
9781467329453Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2012, IEEETitle of proceedings
Proceedings of the 2012 IEEE International Conference on Industrial Engineering and Engineering ManagementEvent
Industrial Engineering and Engineering Management. International Conference (2012 : Hong Kong)Publisher
IEEEPlace of publication
Piscataway, N.J.Usage metrics
Categories
No categories selectedLicence
Exports
RefWorksRefWorks
BibTeXBibTeX
Ref. managerRef. manager
EndnoteEndnote
DataCiteDataCite
NLMNLM
DCDC