Optimization of multi-pass turning operations using genetic algorithms for the selection of cutting conditions and cutting tools with tool-wear effect

A new genetic algorithm-based method is applied to the optimization of cutting conditions and selection of cutting tools in multi-pass turning operations (MPTOs). A comprehensive optimization criterion for MPTOs is developed and used as the objective function integrating the contributing effects of all major machining performance measures in all passes. A new methodology for the allocation of total depth of cut in MPTOs is also developed. The effect of progressive tool wear in optimization processes for MPTOs is included in the current work. Presented case studies demonstrate the application of the new methodology for optimal allocation of the total depth of cut as well as optimization of cutting conditions and the selection of cutting tool inserts, and offer a comparison between optimization processes with and without the effect of tool wear in all passes.