A Relative Assessment of Algorithms in Optimising the Influence of Process Parameters on Turning Process of Grey Cast Iron

Grey cast iron of the grade ASTM 48 is in the use for manufacturing casting parts with low or middle duty or load, such as various stove parts, gas burners, boiler parts, protective cover, hand wheel, brackets, base plate, crane balls, counter weight, handle, machine base etc. The production volume rate is mainly lies with the material removal rate during machining process and this is essential towards fulfilling the demand. Henceforth the maximization of the MRR is indispensable in this regard. This attempt of investigation involves in optimising the MRR of turning operations on ASTM 48 Grey cast iron with the application of six optimization algorithms namely, Particle swarm Optimization, Scatter Search Algorithm, Simulated Annealing Algorithm, Artificial Bee Colony Algorithm, Ant Colony Algorithm and Firefly algorithm. By assessing the simulation performance of the algorithms in terms of MSE the best algorithm is chosen for further analysis and forecast with the hybridization approach of statistically significant relationship integrated in the programme. Machining speed, feed, depth of cut and material removal rate are chosen as the process parameters. Regression equation modeling, analysis and optimization algorithms are used to identify the influences between the parameters and optimized. KeywordsTurning, Grey cast iron of Grade ASTM 48, Regression, Particle swarm Optimization, Scatter Search Algorithm, Simulated Annealing Algorithm, Artificial Bee Colony Algorithm, Ant Colony Algorithm and Firefly algorithm, hybridization, Optimisation, Minitab, MATLAB.