In the present work, an attempt is made to solve multi-objective optimization problem is turning by using a genetic algorithm (GA). Optimization in turning means determination of the optimal set of machining parameters to satisfy the objectives within the operational constraints. These objectives may be minimum production cost per piece, minimum production time per piece or any weighted combination of both. The main machining parameters which are to be considered as variables of the optimization are cutting speed, feed and depth of cut. The optimum set of these three input parameters is determined for a particular job-tool combination of high carbon steel-tungsten carbide during a single-pass turning which minimizes both unit production time as well as unit production cost after satisfying the constraints of power availability, surface roughness condition, tool life, dimensional tolerance and rigidity. A Pareto-optimal front of optimal solutions is obtained by using a GA. The proposed algorithm is found to perform better than a goal programming technique.
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