Electrochemical discharge machining (ECDM) is recognized as a successful method for processing non-conductive materials through thermal erosion and chemical dissolution. This article aims at the development of a finite element modeling (FEM) based three-dimensional (3D) thermal model for estimating the temperature distribution for scrutinizing the material removal rate (MRR) in electrochemical discharge drilling of silica glass material. The predicted FEM results are verified against existing literature and experimental results during micro-drilling operation. Simulations for evaluating the parametric studies such as the effect of applied voltage, electrolyte concentration, electrolyte type, energy partition on MRR is performed. Results revealed that the experimental values of MRR exhibit fare agreement with the predicted FEA results. Experiments are performed using adaptive tool feed based closed-loop ECDM machining that retracts the tool in an upward direction once its contact is detected with the work material. Tool contacts often result in a high tool wear rate (TWR). Moreover, the response surface methodology (RSM) based mathematical models are established to correlate the input variable’s relationship with the response parameters. Tool feed rate, applied voltage, and electrolyte concentration are chosen as numerical input variables while electrolyte type and tool material are chosen as categorical variables. MRR, TWR, and a number of tool contacts (NTC) are chosen as response parameters. A number of tool contacts are selected since it influences both MRR and TWR. The model’s adequacy is checked using the analysis of variance (ANOVA) and found significant for all the responses. The multi-response optimization of distinctive input variables is acquired by utilizing the desirability function (obtained 0.8646) for maximizing the MRR and minimizing the both TWR and NTC.

电化学放电加工（ECDM）被认为是通过热蚀和化学溶解处理非导电材料的成功方法。本文旨在开发一种基于有限元建模（FEM）的三维（3D）热模型，用于估算温度分布，以仔细检查二氧化硅玻璃材料的电化学放电钻孔中的材料去除率（MRR）。预测的有限元结果在微钻孔操作中已根据现有文献和实验结果进行了验证。进行了评估参数研究的仿真，例如施加电压，电解质浓度，电解质类型，能量分配对MRR的影响。结果表明，MRR的实验值与有限元分析的预测结果相符。使用基于自适应工具进给的闭环ECDM加工进行实验，一旦检测到工具与工作材料的接触，该工具便向上拉回工具。刀具接触通常会导致较高的刀具磨损率（TWR）。此外，建立了基于响应面方法学（RSM）的数学模型，以将输入变量的关系与响应参数相关联。选择工具进给速度，施加电压和电解质浓度作为数值输入变量，同时选择电解质类型和工具材料作为分类变量。选择MRR，TWR和许多工具触点（NTC）作为响应参数。选择了许多工具触点，因为它会影响MRR和TWR。使用方差分析（ANOVA）检查模型的适当性，并发现其对所有响应均具有显着性。通过利用需求函数获得独特输入变量的多响应优化（获得0.8646）以最大化MRR和最小化TWR和NTC。