Machining performance optimization during plasma arc cutting of AISI D2 steel: application of FIS, nonlinear regression and JAYA optimization algorithm

摘要: The work focuses on assessing the optimal machining conditions which could simultaneously satisfy multiple process performance indices during of AISI D2 steel. main characteristic that have been considered here for evaluating plasma arc are surface roughness and material removal rate; corresponding parameters cutting speed, gas pressure torch height. study proposes an integrated optimization module combining fuzzy inference system, nonlinear regression JAYA algorithm towards optimizing correlated multi-response features Optimum value found as speed 4000 m/min, 95 psi height 0.5 mm using aforementioned methodology. Application potential aforesaid route has compared to teaching–learning based (TLBO) genetic algorithm. It concluded possesses less convergence time hence execution is faster TLBO