• DocumentCode
    1898224
  • Title

    An On-line Probabilistic Paradigm for Optimal Disassembly Planning

  • Author

    Tang, Ying ; Renner, Peter

  • Author_Institution
    Electr. & Comput. Eng. Dept., Rowan Univ., Glassboro, NJ
  • fYear
    2006
  • fDate
    21-23 June 2006
  • Firstpage
    770
  • Lastpage
    774
  • Abstract
    Disassembly is of growing importance in material and product recovery. However, the deployment of this process is complicated due to the lack of a priori information necessary for its control and planning. This paper develops a predictive model to tackle this problem
  • Keywords
    assembly planning; belief networks; learning (artificial intelligence); optimised production technology; probability; uncertainty handling; Bayesian learning; material recovery; online probabilistic paradigm; optimal disassembly planning; product recovery; Assembly; Cost function; Decision making; Fuzzy systems; Kernel; Manufacturing; Predictive models; Recycling; Reverse logistics; Uncertainty; Bayesian learning; disassembly Petri net; optimal disassembly planning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Service Operations and Logistics, and Informatics, 2006. SOLI '06. IEEE International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    1-4244-0317-0
  • Electronic_ISBN
    1-4244-0318-9
  • Type

    conf

  • DOI
    10.1109/SOLI.2006.329087
  • Filename
    4125679