Optimization of MQL Parameters During Turning for the Minimization of Flank Wear using DoE, PSO and SAA

Abstract

The concept of minimum quantity lubrication (MQL) has come into practice since a decade ago in order to overcome the disadvantages of flood cooling. This experimental investigation deals with the effects of MQL parameters during turning for the minimization of flank wear with surface roughness as constraint. The parameters of MQL selected are density of coolant, mass flow rate of coolant and pressure of air. The selected MQL parameters are varied through four levels. The flank wear values of the cutting inserts after machining are observed and recorded. The best levels of MQL parameters are identified by using Taguchi’s design of experiments. A validation experiment is conducted with the identified best levels of parameters and the corresponding flank wear value is recorded. This analysis further inter-relates the performances of particle swarm optimization and simulated annealing algorithm (SAA). The result obtained from SAA is comparatively better than that of the results obtained from other techniques.