• DocumentCode
    3287858
  • Title

    Setup Planning and Operation Sequencing Using Neural Network and Genetic Algorithm

  • Author

    Joshi, R.S. ; kumar, N. ; Sharma, Anju

  • Author_Institution
    RIMT-IET, Mandi Gobindgarh
  • fYear
    2008
  • fDate
    7-9 April 2008
  • Firstpage
    396
  • Lastpage
    401
  • Abstract
    In process planning setup planning and operation sequencing are the major issues. In setup planning feature having same approach direction & tool commonality are grouped into setup. After making different setups operation sequencing in each setup is done for setup planning neural network is efficient. Operation sequencing problem is converted into the traveling salesman problem in which objective function is to reduce total cost. To solve these issues in an efficient manner Genetic Algorithm technique is more suitable because it is a viable means for searching the solution space of operation sequence providing a computational time on the order of a few seconds. The present work generates the results for the prismatic parts. The presented algorithm for setup planning and operation sequencing is efficient enough for its use as a module within the development of a CAPP system.
  • Keywords
    CAD/CAM; computer aided production planning; genetic algorithms; neural nets; process planning; CAPP system; computer aided design; computer aided process planning system; genetic algorithm; manufacturing system; operation sequencing; process planning setup planning; setup planning neural network; traveling salesman problem; Cost function; Fixtures; Genetic algorithms; Hopfield neural networks; Machining; Neural networks; Process planning; Technology planning; Traveling salesman problems; Unsupervised learning; CAPP; Genetic algorithm; Operation sequencing.; Setup planning; Unsupervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology: New Generations, 2008. ITNG 2008. Fifth International Conference on
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    0-7695-3099-0
  • Type

    conf

  • DOI
    10.1109/ITNG.2008.94
  • Filename
    4492512