Hastelloy-X, a nickel-based heat resistant super alloy, exhibits challenges for manufacturing sectors. During Hastelloy-X machining, elevated temperatures develop at the tool-workpiece interface zone. It promotes tool wear and degrades the surfaces quality. However, their machinability can be enhanced by optimizing machining environments. Machine tools are the principal users of electricity in industrial activities. As a result, economical manufacturing practices are intended to minimize costs. Consequently, the objective is to optimize the turning operations for efficiency, productivity, and sustainability. Al2O3–ZrO2 (Alumina–Zirconia) ceramic inserts were used for the turning experiments on Hastelloy-X. Various machining parameters, including depth of cut, feed rate, and cutting speed, were employed, along with machining environments such as dry, wet, and cryogenic. A total of 9 experiments as per Taguchi’s L9 fractional factorial design were performed. The goal of this study is to find out impact of different machining parameters on material removal rate (MRR), specific cutting energy (SCE), surface roughness (SR), and tool wear rate (WR).A multi-objective model, with parameter weights determined using the Analytical Hierarchy Process (AHP), was developed by applying the “Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)” technique, and its regression analysis was performed. Response surface optimization was implemented to optimize the established multi-objective function and determine the optimal machining conditions. Regression analysis utilizing Response Surface Methodology (RSM) was carried out to optimize the machining parameters. Feed rate shown strong direct correlation with WR, SR, SCE, and MRR, ANOVA results also confirm the same trend. Specific cutting energy, surface roughness, and wear rate improved by 17.17%, 8.72%, and 4%, respectively, under suggested optimal environment, while material removal rate has negligible variation.