In components manufacturing, the Wire EDM is more popular due to its outstanding features of high dimensional accuracy, lower cost of production and good surface finish as there is no physical contact between the wire and work piece. However, for the steel with higher hardness, it is difficult to obtain these features up to the required extent. Moreover, with the help of optimum process parameters selection the WEDM performance characteristics should be improved. The most commonly studied responses for this process are material removal rate (MRR), Surface finish, Kerf width, wire consumption, roundness error. Among these, the responses like Kerf width, MRR and surface roughness are the primary responses. It is observed that pulse on time, pulse off time, servo voltage, peak current and wire feed are the influencing input parameters to these primary responses. Therefore, in the present work, the optimal level of input parameters is estimated for these responses using the Grey-Entropy-Fuzzy (GEF) and Genetic Algorithm (GA) during wire EDM of steel grade DC53 with high hardness of HRC58normally used in stamping dies, injection moulding and compression Moulding etc. To convert the multi objective problem into a single objective, the grey relational coefficient (GRC) has been calculated using Grey Relational Analysis and the weight-age of each response is approximated during the entropy method. To estimate the relation among the input parameters and single objective (GRC) fuzzy mathematical modelling technique termed as GEF has been applied. The optimal performance has been calculated using GA and GEF model is considered as fitness function. Five conformational tests on optimum parameter combination suggested by GA has been performed. The predicted values and experimental values have been found to be in good agreement with a standard error of 3.31% hence the prediction performance of the GREG-Fuzzy is quite satisfactory.

在电火花线切割机中，由于电火花线切割机具有很高的尺寸精度，较低的生产成本和良好的表面光洁度等突出特征，因为电火花线和工件之间没有物理接触，因此受到广泛欢迎。但是，对于具有较高硬度的钢，难以达到所需程度的这些特征。此外，借助最佳工艺参数选择，应改善WEDM性能特征。该过程中最常研究的响应是材料去除率（MRR），表面光洁度，切缝宽度，线消耗，圆度误差。其中，诸如Kerf宽度，MRR和表面粗糙度的响应是主要响应。观察到脉冲接通时间，脉冲断开时间，伺服电压，峰值电流和送丝是这些主要响应的影响输入参数。因此，在目前的工作中，在通常用于冲压模具的具有高硬度HRC58的DC53级钢的电火花线切割过程中，使用灰色熵-模糊（GEF）和遗传算法（GA）估计了这些响应的最佳输入参数水平。为了将多目标问题转换为单个目标，已使用灰色关联分析计算了灰色关联系数（GRC），并在熵方法中估算了每个响应的权重年龄。为了估计输入参数和单目标（GRC）之间的关系，采用了称为GEF的模糊数学建模技术。使用GA计算了最佳性能，GEF模型被认为是适应度函数。GA建议的最佳参数组合已进行了五次构象测试。已发现预测值和实验值与3.31％的标准误差非常吻合，因此GREG-Fuzzy的预测性能非常令人满意。