Intelligent Programming of CNC Turning Operations using Genetic Algorithm

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@Article{Balic:2006:JIM,
  author =       "Joze Balic and Miha Kovacic and Bostjan Vaupotic",
  title =        "Intelligent Programming of CNC Turning Operations
                 using Genetic Algorithm",
  journal =      "Journal of intelligent manufacturing",
  year =         "2006",
  volume =       "17",
  number =       "3",
  pages =        "331--340",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming, CNC
                 programming, GA, Intelligent CAM, Turning, Tool path
                 generation",
  ISSN =         "0956-5515",
  DOI =          "doi:10.1007/s10845-005-0001-1",
  abstract =     "CAD/CAM systems are nowadays tightly connected to
                 ensure that CAD data can be used for optimal tool path
                 determination and generation of CNC programs for
                 machine tools. The aim of our research is the design of
                 a computer-aided, intelligent and genetic algorithm(GA)
                 based programming system for CNC cutting tools
                 selection, tool sequences planning and optimisation of
                 cutting conditions. The first step is geometrical
                 feature recognition and classification. On the basis of
                 recognised features the module for GA-based
                 determination of technological data determine cutting
                 tools, cutting parameters (according to work piece
                 material and cutting tool material) and detailed tool
                 sequence planning. Material, which will be removed, is
                 split into several cuts, each consisting of a number of
                 basic tool movements. In the next step, GA operations
                 such as reproduction, crossover and mutation are
                 applied. The process of GA-based optimisation runs in
                 cycles in which new generations of individuals are
                 created with increased average fitness of a population.
                 During the evaluation of calculated results (generated
                 NC programmes) several rules and constraints like rapid
                 and cutting tool movement, collision, clamping and
                 minimum machining time, which represent the fitness
                 function, were taken into account.

                 A case study was made for the turning operation of a
                 rotational part. The results show that the GA-based
                 programming has a higher efficiency. The total
                 machining time was reduced by 16percent. The demand for
                 a high skilled worker on CAD/CAM systems and CNC
                 machine tools was also reduced.",
}

Genetic Programming entries for Joze Balic Miha Kovacic Bostjan Vaupotic

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