Optimization of EDM process using grey-fuzzy approach

D. Rodić, Marin Gostimirović, M. Sekulić, Branislav Batinić, Nikola M. Laković
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Abstract

The research investigated the optimization of various performance features on the basis of a gray-fuzzy analysis. The goal was to generate an intelligent system for the optimization of electrical discharge machining based on fuzzy logic and gray analysis. Taguchi's L9 experimental design was used as the research methodology. Two input parameters were selected, namely, discharge current and pulse duration. On the other hand, the material removal rate and surface roughness were taken as output machining performances. Depending on the response of the output performances, the input parameters are selected by applying the gray relation grade and signal-to-noise ratio strategy as performance index. The system is set up according to the following criteria: maximum material removal rate and minimum surface roughness. Based on these criteria, the optimal parameters were obtained, i.e. a discharge current of 5 A and a pulse duration of 5 μ. This combination results in a high gray fuzzy degree of 0.521, which is close to the reference value. Considering the results of the validation experiments, it is concluded that a gray-fuzzy approach can be successfully applied to obtain the optimal combination of influential control parameters.
基于灰色模糊方法的电火花加工工艺优化
在灰色模糊分析的基础上,研究了各种性能特征的优化问题。目的是建立一个基于模糊逻辑和灰色分析的智能电火花加工优化系统。采用田口L9实验设计作为研究方法。选择两个输入参数,即放电电流和脉冲持续时间。另一方面,以材料去除率和表面粗糙度作为输出加工性能。根据输出性能的响应,采用灰度关联度和信噪比策略作为性能指标来选择输入参数。该系统是根据以下标准设置的:最大材料去除率和最小表面粗糙度。在此基础上,得到了放电电流为5 a、脉冲持续时间为5 μ的最佳参数。这种组合得到的灰色模糊度较高,为0.521,接近参考值。结合验证实验的结果,得出灰色-模糊方法可以成功地获得影响控制参数的最优组合。
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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