Multi-objective optimization of green technology thermal drilling process using grey-fuzzy logic method

Abstract

Abstract The wastage of metal chips from conventional drilling process creates massive environmental pollution. In order to reduce emission pollution, this process should be replaced by the green technology of thermal drilling process. Thermal drilling is an energy efficient, clean and chip less drilling method that has attracted more automotive and aerospace manufacturers in recent years. The processing time, tool failure and manufacturing cost of drilling are reduced and the bushing formation is three times thicker than the workpiece, which offers a prolonged bearing area that fits a shaft firmly. However, achieving these objectives is time consuming and leads to material waste for industrial sectors. Here, we propose a robust methodology that combines experiments with modern optimization technique in order to solve the industrial challenge and further improve the drilling quality. The experiments were conducted on galvanized steel material with different thicknesses (1 mm, 1.5 mm and 2 mm). Three thermal drilling tools are developed using M2 tool steel with three different geometry angles such as 30 o , 37 . 5 o and 45 o . The recommended level (A3 B1 C2) identified in this experimental research, allows to minimize the thermal drilling parameters with intended benefits of the output parameters. It permits to identify the best solution of minimum surface roughness of 1.088 μm with the roundness error of 0.080 mm and 0.145 mm run-out. Further, the multi-objective decision technique designed offer contribution details of critical input parameters contribution of rotational speed, tool angle, and workpiece as 76.58%, 10.56%, and 1.982%, respectively.