Optimisation of cooling fin parameters in turning by using DoE, AGA and SAA based on cutting zone temperature

In this investigation, externally fabricated metallic cooling fin system has been introduced as an alternative solution to the direct application of coolant in the metal cutting zone. A new parametric study without considering any kind of benchmark problems in this area is performed and methodology has been developed to analyse the effects of different fin parameters such as thickness of cooling fin, length of cooling fin and material of cooling fin on the flank wear of cutting insert. All these parameters are varied through three levels. In this analysis, it is assumed that the selected single point cutting insert is subjected only to static heating in the cutting zone, which deals with the analysis of the effects of heat transfer through metallic cooling fin in turning operation. This analysis interrelates the performances of design of experiments (DoE), regression analysis, adaptive genetic algorithm (AGA) and simulated annealing algorithm (SAA) to obtain the best possible solution. The result of this analysis identifies the optimal values of fin parameters for effective and efficient machining.