The paper presents a new methodology involving the use of genetic algorithms for the selection of optimum cutting conditions and cutting tools in multipass turning operations based on a comprehensive optimization criterion. The optimization objective includes the contributing effects of all major machining performance measures. A hybrid process model, based on metal-cutting theories and numerical interpolation from an experimental database, predicts major machining performance measures. Presented case studies demonstrate the application of the new methodology for the determination of optimum cutting conditions and the selection of cutting tool inserts.
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Wang et al. (2002) studied this question.
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