Dataset for: Physics-informed multi-task deep learning and explainable AI framework for simultaneous prediction of MRR and surface roughness in ECM–EDM of Al–VC composites

This dataset contains experimental results from electrochemical machining (ECM) and electrical discharge machining (EDM) of aluminum–vanadium carbide (Al–VC) composites. The data were used to develop a physics-informed multi-task deep learning framework for simultaneous prediction of material removal rate (MRR) and surface roughness (Ra). The dataset integrates ECM (with and without baffled tools) and EDM experiments into a unified modeling structure. Physical constraints derived from Faraday’s law and discharge energy relations were incorporated during model training. The dataset supports the manuscript submitted to Materials and Manufacturing Processes (Taylor & Francis).