A RFID-case-based sample management system for fashion product development

Choy, King Lun Tommy; Chow, K. K.; Moon, Kirk L.; Zeng, Xuanke; Lau, Henry C. W.; Chan, Felix T. S.; Ho, G.T.S.

doi:10.1016/j.engappai.2008.10.011

Cited by 39 publications

(13 citation statements)

References 25 publications

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“…The results of applying RFID-RMS to the GENCO Distribution System illustrate that the utilisation of warehouse resources is maximised while work efficiency is greatly enhanced. The authors extend their work in Choy et al (2009), andPoon et al (2009).…”

Section: Rfid Technologymentioning

confidence: 98%

An RFID-based digital warehouse management system in the tobacco industry: a case study

Wang

Chen

Xie

2010

International Journal of Production Research

104

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This paper proposes a digital warehouse management system (DWMS) in the tobacco industry based on radio frequency identification (RFID) technology. The DWMS helps warehouse managers to achieve better inventory control, as well as to improve the operation efficiency. In this system, a set of basic events and storage/retrieval rules are defined as event-condition-action (ECA) rules to improve the feasibility and flexibility of DWMS. By using RFID technology, the DWMS enables a plane warehouse to achieve visualised inventory management, automatic storage/retrieval assignment and high accuracy of inventory control as an automatic warehouse. A case in the tobacco industry is studied to illustrate the feasibility and rationality of the proposed system. Based on the ECA rules, a storage/retrieval methodology is proposed to improve the storage/ retrieval operations. The results of this case study illustrate that RFID-DWMS can help a plane warehouse to improve operation efficiency, enhance the utilisation of warehouse capacity, increase inventory accuracy and reduce manpower and loading time significantly.

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Section: Rfid Technologymentioning

confidence: 98%

An RFID-based digital warehouse management system in the tobacco industry: a case study

Wang

Chen

Xie

2010

International Journal of Production Research

104

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“…In process planning, Yang and Wang (2009) have developed a recommender system for software project planning using CBR algorithm, Seo et al (2007) have developed a process planning system using CBR for block assembly in ship building and Changchien and Lin (2005) have designed a CBR system for marketing plans. In Inventory/ supply chain, Poon et al (2009) present a resource management CBR system for managing order-picking operations in warehouses and Choy et al (2009) presents a CBR sample management system for fashion product development.…”

Section: Cbr In Process Planning and Controlmentioning

confidence: 99%

A survey of AI in operations management from 2005 to 2009

Kobbacy

Vadera

2011

Journal of Manufacturing Technology Management

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Purpose: The use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence this paper presents a survey of the use of AI in operations management aimed at presenting the key research themes, trends and directions of research.Design/methodology/approach: The paper builds upon our previous survey of this field which was carried out for the 10 year period 1995 to 2004(Kobbacy et al. 2007. Like the previous survey, it uses the Elsevier's ScienceDirect database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus the application categories adopted are: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Research on utilising neural networks, case based reasoning, fuzzy logic, knowledge based systems, data mining, and hybrid AI in the four application areas are identified. Findings:The survey categorises over 1400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: (a) The trends for Design and Scheduling show a dramatic increase in the use of GAs since 2003-04 that reflect recognition of their success in these areas, (b) A significant decline in research on use of KBS, reflecting their transition into practice, (c) an increasing trend in the use of fuzzy logic in Quality, Maintenance and Fault Diagnosis, (d) surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research.Originality/value: This is the largest and most comprehensive study to classify research on the use of AI in operations management to date. The survey and trends identified provide a useful reference point and directions for future research.

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“…RFID technology is an emerging technology that uses radio waves to keep track of identified objects. In the garment industry, RFID technology are commonly applied in retailing [23,24] and fabric resources management [25,26]. This study differs from many of the previous researches in that it applies RFID technology in production where raw materials or products are of diverse styles, sizes and colors, making management of these items become complex.…”

Section: Literature Reviewmentioning

confidence: 93%

An intelligent system for production resources planning in Hong Kong garment industry

Lee

Choy

Law

et al. 2012

2012 IEEE International Conference on Industrial Engineering and Engineering Management

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Resources 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.

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A RFID-case-based sample management system for fashion product development

Cited by 39 publications

References 25 publications

An RFID-based digital warehouse management system in the tobacco industry: a case study

An RFID-based digital warehouse management system in the tobacco industry: a case study

A survey of AI in operations management from 2005 to 2009

An intelligent system for production resources planning in Hong Kong garment industry

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