Sustainable EDM production of micro-textured die-surfaces: Modeling and optimizing the process using machine learning techniques - Mahanti, Ranajit; Das, Manas (Measurement : journal of the International Measurement Confederation, 2025)
[Display omitted] •Parametric correlation of responses using RSM and ANN modeling in EDM of H13 alloy is studied.•Formulation of a combined objective to minimize surface roughness and overcut is done.•The effectiveness of metaheuristic algorithms (PSO, TLBO) over desirability function-based methods is emphasized.•Sustainability in EDM for fabrication of large-area micro-textured surfaces is explored. The present research explores the role of die-sinking EDM parameters, such as peak current, pulse duration, and gap voltage, and their proper selection for the cost-effective fabrication of negative micro-pillar-textured surfaces using a die-material of H13 steel alloy. The developed artificial neural networks (ANN) models of surface roughness and overcut outperform the response surface methodology models in predicting responses as higher ‘R2 values’ and lower ‘mean squared error’ with ANN models. A lower peak current of 2 A, lower pulse duration of 55.46 µs, and intermediate gap voltage of 37.83 V is selected from metaheuristic optimization approaches such as teaching–learning-based optimization and particle swarm optimization that are efficient and comparable with the desirability function-based approach while finding optimum parameter values. Further, sustainable fabrication of micro-textured H13 die surfaces is carried out on large areas using selected optimized parameters with a form tool electrode. The negative micro-pillar pattern surface demonstrates an average overcut of ∼ 40 ± 15 µm in comparison to the dimensions of the form tool. This research emphasized the sustainability of the EDM process by utilizing reusable dielectric fluid, prioritizing optimal parameters for high-quality fabrication using low electrical-energy utilization, and enabling large-scale production using a form tool.