• DocumentCode
    766147
  • Title

    Fuzzy operator allocation for balance control of assembly lines in apparel manufacturing

  • Author

    Hui, Patrick Chi-Leung ; Chan, Keith C C ; Yeung, K.W. ; Ng, Frency Sau-Fun

  • Author_Institution
    Inst. of Textiles & Clothing, Hong Kong Polytech. Univ., Kowloon, China
  • Volume
    49
  • Issue
    2
  • fYear
    2002
  • fDate
    5/1/2002 12:00:00 AM
  • Firstpage
    173
  • Lastpage
    180
  • Abstract
    Production processes in apparel manufacturing typically involve hybrid assembly lines. In order to perform at predetermined production rates, careful balance control of the sewing operations on these assembly lines is very important. The right number of operators to be moved in and out of a sewing section has to be accurately determined. In this paper, the authors extend the literature on fuzzy logic applications to control systems by proposing a simple, yet effective, rule-based system that captures the knowledge of experienced supervisors in a set of fuzzy rules. These rules specify how balance control can be achieved based on the level of difference between; (1) the actual and target buffer level; and (2) the actual and target section performance. Since these parameters are normally expressed in linguistic terms, they are encoded in rules expressed with fuzzy logic. The number of operators to be moved in and out of a sewing section can, therefore, be determined by means of fuzzy inferences. To evaluate the effectiveness of the system, we compared its performance to the decisions made by experienced supervisors at a large shirt factory. The system was found to increase in production efficiency by 30%
  • Keywords
    assembling; control system synthesis; fuzzy control; inference mechanisms; knowledge based systems; process control; textile industry; apparel manufacturing; fuzzy inferences; fuzzy logic control systems; fuzzy rules; hybrid assembly lines; knowledge capture; production efficiency; production processes; production rates; rule-based system; sewing operations; Assembly; Control systems; Fuzzy control; Fuzzy logic; Fuzzy sets; Fuzzy systems; Knowledge based systems; Manufacturing processes; Production facilities; Production systems;
  • fLanguage
    English
  • Journal_Title
    Engineering Management, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9391
  • Type

    jour

  • DOI
    10.1109/TEM.2002.1010885
  • Filename
    1010885