• DocumentCode
    2544384
  • Title

    A multiple objective optimization model for environmental benign process planning

  • Author

    Jin, Kai ; Zhang, Hong C. ; Balasubramaniam, Prabhaakar ; Nage, Switesh

  • Author_Institution
    Texas A&M Univ. Kingsville, Kingsville, TX, USA
  • fYear
    2009
  • fDate
    21-23 Oct. 2009
  • Firstpage
    869
  • Lastpage
    873
  • Abstract
    Few years back, not much importance was given to the effect of the product on the environment in the process planning stage. Till recently the environmental issues related with the manufacturing process were taken up seriously by both the general public and the government agencies which led to the need for environmental conscious manufacturing. This paper deals with the systematic determination of methods involved in the manufacturing of parts with one of the objective of minimizing environmental impacts. The focus of this study is to develop a multi objective non linear programming model for environmental supportive process planning while minimizing factors such as machining cost, machining time and environmental impact. An interactive front end tool is developed for optimum parameter selection and the results are discussed.
  • Keywords
    environmental management; nonlinear programming; process planning; environmental benign process planning; environmental conscious manufacturing; environmental supportive process planning; interactive front end tool; manufacturing process; multiobjective nonlinear programming model; multiple objective optimization model; Costs; Environmental factors; Government; Linear programming; Machining; Manufacturing processes; Mathematical model; Process planning; Production; Pulp manufacturing; Conformance Cost; Internal And External Failure Cost; Non Conformance Cost; Total Quality Cost;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management, 2009. IE&EM '09. 16th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-3671-2
  • Electronic_ISBN
    978-1-4244-3672-9
  • Type

    conf

  • DOI
    10.1109/ICIEEM.2009.5344194
  • Filename
    5344194