N of Process Parameters for Turning Hastelloy X beneath Diverse Machining Environments Applying Evolutionary Algorithms: A Comparative StudyVinothkumar Sivalingam 1 , Jie Sun 1 , Siva Kumar Mahalingam two , Lenin Nagarajan two, , Yuvaraj Natarajan two , Sachin Salunkhe 2 , Emad Abouel Nasr three , J. Paulo Davim 4 and Hussein Mohammed Abdel Moneam Hussein 5,Citation: Sivalingam, V.; Sun, J.; Mahalingam, S.K.; Nagarajan, L.; Natarajan, Y.; Salunkhe, S.; Nasr, E.A.; Davim, J.P.; Hussein, H.M.A.M. Optimization of Course of action Parameters for Turning Hastelloy X beneath Different Machining Environments Applying Evolutionary Algorithms: A Comparative Study. Appl. Sci. 2021, 11, 9725. ten.3390/ app11209725 Academic Editor: Vladimir Modrak Received: six September 2021 Accepted: 11 October 2021 Published: 18 OctoberKey Laboratory of High-Efficiency and Clean Mechanical Manufacture, National Demonstration Center for Experimental Mechanical Engineering Education, School of Mechanical Engineering, Shandong University, Jinan 250061, China; svkceg@gmail (V.S.); [email protected] (J.S.) Division of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R D Institute of Science and Technologies, Chennai 600 062, Tamilnadu, India; lawan.sisa@gmail (S.K.M.); [email protected] (Y.N.); [email protected] (S.S.) Industrial Engineering Division, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia; [email protected] Division of Mechanical Engineering, Campus Universit io de Santiago, JPH203 custom synthesis University of Aveiro, 3810-193 Aveiro, Portugal; [email protected] Department of Mechanical Engineering, Faculty of Engineering, Psalmotoxin 1 Description helwan University, Cairo 11732, Egypt; [email protected] Department of Mechanical Engineering, Faculty of Engineering, Ahram Canadian University, 6th of October City 19228, Egypt Correspondence: n.lenin@gmail; Tel.: 91-9976-9096-Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.Abstract: Within this research function, the machinability of turning Hastelloy X with a PVD Ti-Al-N coated insert tool in dry, wet, and cryogenic machining environments is investigated. The machinability indices namely cutting force (CF), surface roughness (SR), and cutting temperature (CT) are studied for the diverse set of input course of action parameters such as cutting speed, feed price, and machining atmosphere, by means of the experiments conducted as per L27 orthogonal array. Minitab 17 is made use of to create quadratic Multiple Linear Regression Models (MLRM) according to the association among turning parameters and machineability indices. The Moth-Flame Optimization (MFO) algorithm is proposed in this perform to recognize the optimal set of turning parameters by way of the MLRM models, in view of minimizing the machinability indices. Three case studies by thinking about individual machinability indices, a mixture of dual indices, along with a mixture of all three indices, are performed. The suggested MFO algorithm’s effectiveness is evaluated in comparison towards the findings of Genetic, Grass-Hooper, Grey-Wolf, and Particle Swarm Optimization algorithms. In the final results, it’s identified that the MFO algorithm outperformed the others. In addition, a confirmation experiment is conducted to verify the outcomes with the MFO algorithm’s optimal mixture of turning parameters. Keywords and phrases: Hastelloy X; turning; cutting force; surface roughness; liquid nitrogen; grass-hooper optimization algorithm; moth-flame.