Optimization of Minimum Quantity Liquid Parameters in Turning for the Minimization of Cutting Zone Temperature

The use of cutting fluid in manufacturing industries has now become more problematic due to environmental pollution and health related problems of employees. Also the minimization of cutting fluid leads to the saving of lubricant cost and cleaning time of machine, tool and work-piece. The concept of minimum Quantity Lubrication (MQL) has come in to 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 cutting zone temperature by considering surface roughness as constraint. The selected MQL parameters are varied through four levels. The maximum temperature values during machining in all the test conditions as per L16 orthogonal array are recorded. The best levels of selected MQL parameters for the minimization of cutting zone temperature were identified by using Taguchi’s Design of Experiments. A validation experiment is conducted with the identified best levels of parameters and the corresponding cutting zone temperature is recorded. This analysis further inter-relates the performances of Particle Swarm Optimization (PSO), Simulated Annealing Algorithm (SAA) and Differential Evolution (DE) for the minimization of cutting zone temperature. The results obtained from DE are comparatively better than that of the results obtained from other techniques.