• DocumentCode
    2417235
  • Title

    Establish An Adaptive (s,S) Production System Under Imperfect Production Conditions By Fuzzy Analytic Hierarchy Process

  • Author

    Chen, Yee-Ming ; Lin, Chun-Ta ; Lo, Chih-Yao ; Wu, Chen-Feng ; Chang, Yu-Teng

  • Author_Institution
    Yuan-Ze Univ., Taoyuan
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    962
  • Lastpage
    968
  • Abstract
    Traditionally, the EPQ model is the most widely used method to solve the production problem. This model is based on ideal production process conditions, with the final products within the specifications and without any defects and the result is significantly different from the actual production system. In reality, a manufacturer encounters a number of uncertainties, such as quality variance, equipment unreliability, and defects and shortage incurred from imperfect production planning, implementation, and processing. Over the past few decades, majority of related EQP studies, based on a single factor or multiple factors, were too complicated to use. This publication is intended to investigate the possible alternatives on imperfect production and quality variance in the production environment by using Fuzzy AHP to evaluate the most critical alternatives. The EPQ model based on these critical factors will determine the alternatives for the optimum Economic Production Quantity, meanwhile an adaptive (s, S) production system can be determined accordingly.
  • Keywords
    adaptive systems; fuzzy set theory; industrial economics; production planning; statistical analysis; EPQ model; adaptive production system; equipment unreliability; fuzzy analytic hierarchy process; optimum economic production quantity; production planning; production process condition; quality variance; Adaptive systems; Cost function; Environmental economics; Fuzzy systems; Manufacturing processes; Production planning; Production systems; Raw materials; Uncertainty; Waste materials;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2006 IEEE International Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9488-7
  • Type

    conf

  • DOI
    10.1109/FUZZY.2006.1681827
  • Filename
    1681827