RSM design-based hybrid approach to multi-response optimization in milling Ti-6Al-4 V alloy: A comparative study

The Selection of appropriate process parameters in milling Ti-6Al-4 V alloy to reduce energy and power consumption while maintaining product quality and process stability is challenging. This study aims to optimize process parameters in milling Ti-6Al-4 V alloy with five primary criteria i.e., average cutting force, shear stress, specific cutting energy, power consumption, and average surface roughness. A total of 26 experimental tests was carried out with the variation of process parameters such as cutting speed (m/min), feed rate (mm/min), and depth of cut (mm) based on the Box-Behnken design (BBD) matrix of response surface method (RSM) under dry and high-pressure cooling (HPC). The criteria importance through the inter-criteria correlation (CRITIC) method was used to determine the relative weights of each response. At the same time, the evaluation of optimum process parameters was done by hybrid multi-response optimization (MRO) techniques such as complex proportional assessment (CRITIC-COPRAS), additive ratio assessment (CRITIC-ARAS), combined compromise solution (CRITIC-COCOSO) and technique for order of preference by similarity to ideal solutions (CRITIC-TOPSIS). After the evaluation, a cutting speed of 32 m/min, feed rate of 22 mm/min, and 0.75 mm depth of cut with HPC were selected as the optimum process parameters. Due to the lack of an identical solution, the sensitivity of the used MRO methods was checked out with the weight variation of the selected criteria. TOPSIS was noticed as the most robust MRO method with less sensitivity. Spearman’s Correlation coefficient was used to assess the correlation among the used hybrid MRO methods.