Multi-objective optimization of turning operation of stainless steel using a roulette wheel optimization algorithm

This study looked at the L-9 orthogonal group design with the following machining process parameters: spindle cutting velocity, peak apparatus temperature, depth of cut, surface irregularity, feed rate, forces generated during cutting, power consumption, materials removal rate (MRR), and heat rate. The operation's surface finish and material removal rate (MRR) were studied using the machining method. The degree of roughness is crucial for determining wear, friction, and material removal rate (MRR), all of which improve process efficiency. AISI-52100 steel was used to manufacture EN-31 steel. The Roulette-Wheel Optimization Algorithm was employed in the current study to optimize (RWOA). MATLAB has been chosen as the testing program.