Surface roughness and surface crack length prediction using supervised machine learning–based approach of electrical discharge machining of deep cryogenically treated NiTi, NiCu, and BeCu alloys

This study aims to investigate the impact of various input variables in electrical discharge machining (EDM) on specific responses, including surface crack length (SCL) and surface roughness (SR). The variables under scrutiny are the electrical conductivity of the workpiece tool, pulse-on time, gap...

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