Environmental, Economical and Technological Analysis of MQL-Assisted Machining of Al-Mg-Zr Alloy Using PCD Tool

Clean technological machining operations can improve traditional methods’ environmental, economic, and technical viability, resulting in sustainability, compatibility, human-centered machining. This, this work focuses on sustainable of Al-Mg-Zr alloy with minimum quantity lubricant (MQL)-assisted using a polycrystalline diamond (PCD) tool. The effect various process parameters the surface roughness cutting temperature were analyzed. Taguchi L25 orthogonal array-based experimental design has been utilized. Experiments have carried out MQL environment, pressure was maintained at 8 bar. multiple responses optimized desirability function analysis (DFA). Analysis variance (ANOVA) shows that speed depth cut are most prominent factors for temperature. Therefore, DFA suggested that, to attain reasonable response values, lower moderate value cut, feed rate appreciable. An artificial neural network (ANN) model four different learning algorithms used predict Apart from this, address sustainability aspect, life cycle assessment (LCA) MQL-assisted dry out. Energy consumption, CO2 emissions, processing time determined results showed MQL-machining required very nominal amount fluid, which produced smaller carbon footprint. Moreover, little energy consumption is achieve high material removal low tool change.