Ti-6Al-4V Extra Low Interstitial (ELI) exhibits superior properties because of controlled interstitial element of iron and oxygen. The effects of four cutting parameters namely cutting speed, feed, depth of cut and tool nose radius on responses like cutting force, average cutting temperature and surface roughness have been investigated for turning of Ti-6Al-4V (ELI). Total 81 experiments have been performed in dry environment. Grey Relational Analysis has been used for multi-objective optimization. Analysis of Variance test has been carried out to investigate contribution of input parameters. The model was found fit with R-Square value of 88.74%. Regression and ANN models are developed for prediction and compared. From the Grey relational analysis, it is clear that optimum parameters to minimize cutting force, cutting temperature and surface roughness while turning Ti-6Al-4V (ELI), are cutting speed as 140 rpm, Nose radius 1.2mm, Feed 0.051mm/rev and depth of cut is 0.5mm. In comparison of regression model, the ANN model is found to be more accurate with average error of 3.57%.

Inconel 600 is a super alloy known for its properties like low thermal conductivity and work hard-ening. The work hardening property of this alloy makes it harder and harder during successive passes of the tool during machining. Therefore, machining of this type of material demands inno-vation in tool material, selection of proper combination of parameters and their levels for economical machining. Coated carbide tool inserts are most widely used for machining Inconel alloys. These inserts are coated with special materials by PVD or CVD technique to reduce flank wear, improve surface finish of machined components and increase the material removal rate (MRR). In this work carbide insert coated with nanocomposite coatings like AlTiN and TiAlSiN commercially known as Hyperlox and HSN2 were used and their performance during machining of Inconel 600 was studied. As improper selection of process parameter influences on the quality of products and productivity, it is important to identify the optimum combination of input process parameters. Most of the time the influence of the input process parameters on the output parameters like MRR, surface roughness and flank wear is studied independently. Information obtained through single objective optimization may not be sufficient because industries desire to optimize all the output parameters, simultaneously. Multi-objective optimization is the only solution to satisfy the requirements of industries and genetic algorithm based multi-objective optimization is adopted in this work in order to get the optimum combination of input process parameters to obtain maximum material removal rate, minimum surface roughness and minimum flank wear simultaneously.

Turning is the utmost elementary process among several CNC machine tool operations which is a versatile, efficient and widely used in industries including mechanical, aerospace and automotive sectors. Most frequently the manufacturing industries face the problem of cutting down the production cost without any oblation in the quality of products. Selection of process parameter is essential for assuring a quality product. Convenient choice of the cutting conditions, parameters and tools for the maximum Material removal rate (MRR) and surface finish needs a sophisticated approach adopting mathematical and statistical models as well as experimental method. Taguchi’s method is a very compelling tool to optimize the process variables. The intention of the present study is to determine surface roughness (Ra) and MRR which are key responses to justify the quality of turning operation. Four process parameters have been selected viz. Nose radius (NR), depth of cut (DOC), feed rate (FR) and spindle speed or cutting speed (CS) that influences these responses. During machining operations, the influence of the process parameters and their interac-tion have been analyzed using a statistical tool ANOVA. Aluminum alloy is widely acceptable by industries owing to its good strength to weight ratio, high resistance to corrosion, malleability and excellent resistance during elevated temperatures.