Ecological design optimization of nozzle parameters for burnishing operation

The design configuration of the nozzle has a vital role in performance measures machining processes. However, parameter optimizations are primary considerations published works. This study optimizes parameters to minimize environmental impacts and enhance surface quality for diamond burnishing (DB) operation. considered energy efficiency (ED), noise emission (NE), total height profile roughness (Rt). variables inner diameter (D), spraying distance (S), pitch angle (P). optimal Taguchi-based Bayesian regularized feed-forward neural network (TBRFFNN) was applied propose models. CRITIC approach is utilized compute weight values responses, while desirability (DA) employed select optimality. observed results D, S, P were 3.0 mm, 15 45 deg., respectively. ED enhanced by 12.7%, RT NE decreased 24.4% 9.1%, respectively, as compared original parameters. obtained outcomes could be practice boost technical characteristics. developed optimizing deal with optimization problems different processes