WSEAS Transactions on Applied and Theoretical Mechanics
Print ISSN: 1991-8747, E-ISSN: 2224-3429
Volume 21, 2026
Analysis and Optimization of Electrode Wear Rate in EDM Using Graphite Electrodes: A Statistical and GPR-Based Approach
Authors: , , ,
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Abstract: This study investigates the effects of key process parameters and graphite electrode types on the axial electrode wear rate (HWR) in electrical discharge machining (EDM). A series of controlled experiments was conducted to evaluate the statistical significance of input variables using analysis of variance (ANOVA). A second-order regression model was developed to quantify the relationship between the machining parameters and HWR. To enhance predictive accuracy and enable efficient optimization, a Gaussian Process Regression (GPR) model was constructed based on the experimental data. The GPR model demonstrated superior prediction capability compared to traditional regression models. Optimal process conditions for minimizing electrode wear were identified using the trained surrogate model. The proposed methodology provides a robust framework for predicting and reducing electrode wear in EDM applications involving graphite electrodes.
Keywords:
EDM, Electrode wear, Graphite electrode, Axial wear rate (HWR), Regression modeling, Gaussian Process Regression (GPR), Process optimization
Pages: 69-76
DOI: 10.37394/232011.2026.21.7