Genetic Algorithm For Multi-Objective Optimization in Sculptured Dies-Cavity Roughing

Ineu Widaningsih, Suprayogi Suprayogi, Anas Ma’ruf, Dradjad Irianto

Abstract


Sculptured-dies Cavity Roughing (SDCR) problem is a multi-dimensional problem. In XY-single cutter problem, the decision variables consist of layering and tooling selection problem by maximizing the efficiency of roughing, which consider finishing efficiency. The previous research approach to this problem shows that the dynamic programming approach. However, it is effective in searching solutions for the time-to-volume coefficient minimization (TVC) problem, and empirically shows 10% improvement compared to machining time minimization objective. The pre-processing procedures in dynamic programming approach are quite complex time-consuming. Applying a genetic algorithm procedure for the multi-dimensional problem (GAMD) guarantees the merging process's feasibility, these pre-processing procedures can be eliminated, and significantly faster computational time. In the 7-3-3 problem chosen in this research, the computational time is reduced from about 2 hours to 30 seconds.

Keywords


Sculptured-dies Cavity Roughing, genetic algorithm, tool selection, Cutting layer determination, time-to-volume coefficient.

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References


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DOI: http://dx.doi.org/10.33021/icsecc.v1i1.4172

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