Performance-based optimal selection of cutting conditions and cutting tools in multipass turning operations using genetic algorithms

Contour finish turning operations with coated grooved tools: Optimization of machining performance

“…Simulated annealing (SA) method was used to solve this optimization problem. Wang et al (2002) extended their previous work (Da et al, 1995(Da et al, , 1996 to multi-pass turning operations. Since the total depth of cut through the passes was fixed, feasible region of this problem became very tight comparing to single pass problems.…”

A review of optimization techniques in metal cutting processes

“…Chowdhury, Pratihar, and Pal (2002) apply a GA-based optimization technique for near optimal cutting conditions selection in a single-pass turning operation, and claim that GA outperform goal programming technique in terms of unit production time at all the solution points. Wang, Da, Balaji and Jawahir (2002) apply GA-based technique for near-optimal cutting conditions for a two-and three-pass turning operation having multiple objectives. Cus and Balic (2003) use GA-based technique to determine the optimal cutting conditions in NC-lathe turning operation on steel blanks that minimize the unit production cost without violating any imposed cutting constraints.…”

Development of hybrid predictive models and optimization techniques for machining operations

“…Major machining performance measures, which directly depend on the cutting parameters, including surface roughness, cutting force, chip form/chip breakability, tool-life and material removal rate, are predicted using a hybrid model in terms of cutting conditions: cutting speed, feed and depth of cut [72]. The early work for single-pass turning, which includes the effect of progressive tool-wear [64], and the subsequent work involving the establishment of a performance-based criterion for the selection of optimum cutting conditions and cutting tool selection [71], have more recently been extended to cover multi-pass turning using genetic algorithms [73]. Fig.…”