Multi-Objective Optimization for Milling Operations using Genetic Algorithms under Various Constraints

Li-Bao An, Peiqing Yang, Hong Zhang, Ming-Ying Chen
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引用次数: 9

Abstract

In this paper, the parameter optimization problem for face-milling operations is studied. A multi-objective mathematical model is developed with the purpose to minimize the unit production cost and total machining time while maximize the profit rate. The unwanted material is removed by one finishing pass and at least one roughing passes depending on the total depth of cut. Maximum and minimum allowable cutting speeds, feed rates and depths of cut, as well as tool life, surface roughness, cutting force and cutting power consumption are constraints of the model. Optimal values of objective function and corresponding machining parameters are found by Genetic Algorithms. An example is presented to illustrate the model and solution method.
基于遗传算法的多种约束条件下铣削作业多目标优化
本文研究了面铣削加工的参数优化问题。建立了以单位生产成本和总加工时间最小、利润率最大化为目标的多目标数学模型。根据切割的总深度,通过一次精加工和至少一次粗加工来去除不需要的材料。最大和最小允许切削速度,进给量和切削深度,以及刀具寿命,表面粗糙度,切削力和切削功耗是模型的约束条件。利用遗传算法求出目标函数的最优值和相应的加工参数。给出了一个算例来说明模型和求解方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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