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
Link To Document :
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