Optimization of cutting process by GA approach

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  author =       "Franci Cus and Joze Balic",
  title =        "Optimization of cutting process by GA approach",
  journal =      "Robotics and Computer-Integrated Manufacturing",
  year =         "2003",
  volume =       "19",
  number =       "1-2",
  pages =        "113--121",
  month =        feb # "-" # apr,
  keywords =     "genetic algorithms, genetic programming, Cutting
                 parameters, Manufacturing, simulation",
  ISSN =         "0736-5845",
  DOI =          "doi:10.1016/S0736-5845(02)00068-6",
  abstract =     "The paper proposes a new optimization technique based
                 on genetic algorithms (GA) for the determination of the
                 cutting parameters in machining operations. In metal
                 cutting processes, cutting conditions have an influence
                 on reducing the production cost and time and deciding
                 the quality of a final product. This paper presents a
                 new methodology for continual improvement of cutting
                 conditions with GA. It performs the following: the
                 modification of recommended cutting conditions obtained
                 from a machining data, learning of obtained cutting
                 conditions using neural networks and the substitution
                 of better cutting conditions for those learned
                 previously by a proposed GA. Experimental results show
                 that the proposed genetic algorithm-based procedure for
                 solving the optimisation problem is both effective and
                 efficient, and can be integrated into an intelligent
                 manufacturing system for solving complex machining
                 optimisation problems.",
  notes =        "http://www.elsevier.com/wps/find/journaldescription.cws_home/704/description#description",

Genetic Programming entries for Franci Cus Joze Balic