Thermal Friction Drilling Process Parametric Optimization for AISI 304 Stainless Steel Using an Integrated Taguchi-Pareto–Grey Wolf-Desirability Function Analysis Optimization Technique

Thermal friction estimations are presently essential on steel for manufacturing applications as they predict the aggregated energy required process. However, current thermal estimates inaccurate exclude optimized thresholds of both input and output quantities. In this article, optimization drilling operation process is accounted by introducing a new method combined Taguchi-Pareto–grey wolf-desirability function analysis applied AISI 304 stainless steel. An objective was formulated using delta values developed from average signal-to-noise into response table Taguchi method. Besides, ranks parameters through taken in reciprocal mode to evaluate linear program according some constraints system. Six were considered tool cylindrical region diameter, angle, contact area ratio, mouthpiece thickness, feed rate speed. The outputs axial force, radial hole diameter dimensional error, roundness error bushing length. These inputs analyzed Based results, which solved C++ software, best value converges iteration 8 with starting 1699.2. Iteration 1 drops 11016.3 six iterations (iterations 2 7) finally at 11015.9 20. usefulness effort help engineers execute cost-effective conservation decisions that could be obtained values.