• Title of article

    Evolutionary approach for cutting forces prediction in milling

  • Author/Authors

    M. Kovacic، نويسنده , , J. Balic، نويسنده , , M. Brezocnik، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2004
  • Pages
    6
  • From page
    1647
  • To page
    1652
  • Abstract
    Knowing cutting forces is important for choosing cutting parameters for milling. Traditionally, cutting forces are calculated by equation which includes empirically measured specific cutting forces. In the article modelling of cutting forces with genetic programming is proposed, which imitates principles of living beings. Measurements have been made for two materials (aluminium alloy AlMgSi1 and steel 1.2343) and two different types of milling (conventional milling and STEP milling). For each material and type of milling parameters, tensile strength and hardness of workpiece, tool diameter, cutting depth, spindle speed, feeding and type of milling were monitored, and for each combination of milling parameters cutting forces were measured. On the basis of the experimental data, different models for cutting forces prediction were obtained by genetic programming. Research shows that genetically developed models fit the experimental data.
  • Keywords
    Milling cutting forces prediction , Genetic programming
  • Journal title
    Journal of Materials Processing Technology
  • Serial Year
    2004
  • Journal title
    Journal of Materials Processing Technology
  • Record number

    1178896