Multi-Objective Optimization of Eco-Friendly MQL Assisted Machining

Abstract

Today, the use of super alloys ranges from commercial to military grade parts. This is due to their properties such as high strength-to-weight ratio, high corrosion resistance, and low thermal expansion. The various applications of super alloys are spanned across aerospace, automobile, chemical and power generation plants, and other major industries. Titanium alloys such as Ti-6Al-4V, and nickel alloys such as INCONEL 718 and waspaloy are categorised as super alloys. Dry machining is preferred over other types of machining. But high forces are required to machine these materials. This results in high tool wear and higher amount of heat generation. High tool wear and heat generation adversely affect the quality of the finished part or component. To reduce high temperature at cutting zone resulting from high heat generation, cutting fluids are used. The problem in using conventional cutting fluid is the cost, and hazardous effect on the operator and the environment. Cutting fluids account for 15% while tooling costs accounts for 4% out of the total production cost in the industries. Due to this hazardous nature of cutting fluids to the environment as well as human life, more sustainable solution is required. Minimum quantity lubrication (MQL) uses very low amount of lubrication (10 - 250 ml/h). Generally natural oils such as vegetable oil, castor oil, etc. are used in MQL. Due to this near dry machining can be obtained while getting the advantages of cutting fluid and lubrication and avoiding hazardous effects. In this study, turning operations were carried out on AISI 4140 using carbide coated insert and using castor oil for minimum quantity lubrication. The experiment was carried out using Taguchi design of experiments L9 orthogonal array. Cutting speed, feed rate and depth of cut were selected as input parameters while surface roughness, power consumption and cutting temperature were selected as output responses. Jaya algorithm which requires only the common control parameters and does not require any algorithm-specific control parameters was ultilized for the multi-objective optimization of output responses. The optimum results were achieved at high cutting speed, low feed rate and high depth of cut.