Genetic equation for the prediction of tool-chip contact length in orthogonal cutting

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "M. Zadshakoyan and V. Pourmostaghimi",
  title =        "Genetic equation for the prediction of tool-chip
                 contact length in orthogonal cutting",
  journal =      "Engineering Applications of Artificial Intelligence",
  volume =       "26",
  number =       "7",
  pages =        "1725--1730",
  year =         "2013",
  month =        aug,
  keywords =     "genetic algorithms, genetic programming, Cutting
                 parameters, Machining, Tool-chip contact length",
  ISSN =         "0952-1976",
  DOI =          "doi:10.1016/j.engappai.2012.10.016",
  URL =          "",
  abstract =     "In metal cutting, it has been acknowledged that the
                 tool-chip contact length significantly affects many
                 aspects of machining such as chip formation, cutting
                 forces, cutting temperatures, tool wear and tool life.
                 Important decrease in the tool-chip contact length,
                 decreases the thickness of the secondary shear zone,
                 which leads to a decrease of the cutting temperature
                 and cutting force. As a result, it has a great effect
                 on finish surface and tool life. Several ways have been
                 proposed in different works to find its value, which
                 have given discordant results for the same set of
                 cutting conditions. In this paper, the genetic equation
                 for the tool-chip contact length is developed with the
                 use of the experimentally measured contact length
                 values and genetic programming. The suggested equation
                 has shown to correspond well with experimental data in
                 various machining conditions with associated cutting
                 parameters and this model predicts tool-chip contact
                 length better than other known solutions.",

Genetic Programming entries for Mohammad Zadshakoyan Vahid Pourmostaghimi