Genetic Programming and Soft-Annealing Productivity

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@Article{Kovacic:2011:MTAEC9,
  author =       "Miha Kovacic and Bozidar Sarler",
  title =        "Genetic Programming and Soft-Annealing Productivity",
  title2 =       "Genetsko Programiranje in Produktivnost Mehkega
                 Zarjenja",
  journal =      "Materials and technology",
  journal2 =     "Materiali in tehnologije",
  year =         "2011",
  volume =       "45",
  number =       "5",
  pages =        "427--432",
  month =        sep # "-" # oct,
  keywords =     "genetic algorithms, genetic programming, steel, soft
                 annealing, furnace productivity, hardness, modelling,
                 jeklo, mehko zarjenje, produktivnost peci, trdota,
                 modeliranje, genetsko programiranje",
  ISSN =         "1580-2949",
  URL =          "http://mit.imt.si/Revija/izvodi/mit115/kovacic.htm",
  URL =          "http://mit.imt.si/Revija/izvodi/mit115/kovacic.pdf",
  size =         "6 pages",
  abstract =     "An optimal thermo-mechanical processing in the steel
                 industry is difficult because of the multi-constituent
                 and multiphase character of commercial steels, the
                 variety of the possible processing paths and the
                 plant-specific equipment characteristics. This paper
                 shows a successful implementation of the genetic
                 programming approach for increasing the furnace
                 conveyor speed and consequently the higher productivity
                 of the heat-treatment furnace in the soft-annealing
                 process. The data (222 samples covering 24 different
                 steel grades) on a furnace conveyor's speed, the
                 chemical composition of the steel (weight percent of C,
                 Cr, Mo, Ni and V) and the Brinell hardness before and
                 after the soft annealing were collected during daily
                 production. On the basis of the measured data a
                 mathematical model for the hardness after the soft
                 annealing was developed by genetic programming.
                 According to the modelled influences on the hardness, a
                 higher furnace conveyor speed was attempted in
                 practice. The experimental results of the hardness
                 after the soft annealing with the increased conveyor
                 speed and the predictions of the mathematical model
                 were compared with an agreement of 3.24 percent (2.68
                 percent at testing data set). The genetic model was
                 also compared and verified with a linear regression
                 model. As a consequence of the used computational
                 intelligence approach, the productivity of the
                 soft-annealing process increased (from the furnace
                 conveyor speed 3.2 m/h to 7 m/h).",
  notes =        "In english http://mit.imt.si/Revija/

                 1 STORE STEEL d.o.o., Zelezarska cesta 3, SI-3220
                 Store, Slovenia

                 2 Laboratory for Multiphase Processes, University of
                 Nova Gorica, Vipavska 13, SI-5000, Nova Gorica,
                 Slovenia",
}

Genetic Programming entries for Miha Kovacic Bozidar Sarler

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