Process parameters optimization by bat inspired algorithm of CNC turning on EN8 steel for prediction of surface roughness

Due to its high precision, productivity, and surface quality, computer numerical control turning (CNC) is a desirable processing tool in the traditional area. CNC machining procedures have huge number of process parameters, making it challenging find best combination parameters for increased accuracy. In this research work, Taguchi method ANOVA were used study effects EN8 steel turning: Surface roughness (Ra) value component affected due cutting speed, depth cut feed rate. Three-level three-parameter experimental design, using Minitab 17 software L9 orthogonal array, coated carbide insert tools, signal-to-noise ratio (S/N) performance characteristics turning. study, statistical approaches such as (S/N ratio) analysis variance (ANOVA) explore cut, rate on roughness. Nature-inspired algorithms play vital role solving real life. bat algorithm can be predict optimal parameters. Verify results by conducting confirmation experiments. The current shows that most important factor affecting