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A series of experiments were conducted to study the performance of a coated cemented carbide tool in high speed milling of Ti-6Al-4V alloy. Experimental measurements of three components of the cutting forces were performed by using a three-component dynamometer. The cutting temperature was measured by using an infrared thermal imager. The variation of cutting forces and cutting temperature with the cutting parameters are investigated. The influence of cutting speed, axial depth of cut, and feed rate on the cutting forces and cutting temperature are analyzed and discussed. The wear patterns of the tool were investigated using scanning electron microscope (SEM) and analysis of energy spectrum, and the wear mechanism is discussed. It is found that abrasive wear and adhesive wear are the dominant wear mechanism of the tool.

Tool wear of a cutting tool has a significant impact on the tool life and surface quality of the finished product. Tool wear is influenced by many factors such as cutting parameters, tool geometry, coating type, work piece material, chatter, and cutting condition. In the present work, the design of experiments (DOE) technique has been used for four factors at five levels to conduct experiments. Tool wear is taken as the response variable measured during end milling, while helix angle, spindle speed, feed and depth of cut are taken as the input parameters. The material and tool selected for this study are AISI 304 stainless steel and uncoated solid carbide end mill cutter respectively. The tool wear was measured using tool maker's microscope. The experimental values are used in six sigma software for finding the coefficients to develop the regression model. The direct and interaction effect of the machining parameter with tool wear were analyzed using contour graphs, which helped to select process parameters for reducing tool wear and also ensure quality of milling.

In the present work, the performances of TiAlN-, AlCrN- and AlCrN/TiAlN-coated and uncoated tungsten carbide cutting tool inserts are evaluated from the turning studies conducted on EN24 alloy steel workpiece. The output parameters such as cutting forces, surface roughness and tool wear for TiAlN-, AlCrN- and AlCrN/TiAlN-coated carbide cutting tools are compared with uncoated carbide cutting tools (K10). The design of experiment based on Taguchi’s approach is used to obtain the best turning parameters, namely cutting speed ($V$), feed rate ($f$) and depth of cut ($d$), in order to have a better surface finish and minimum tool flank wear. An orthogonal array (L${}_9)$ was used to conduct the experiments. The results show that the AlCrN/TiAlN-coated cutting tool provided a much better surface finish and minimum tool flank wear. The minimum tool flank wear and minimum surface roughness were obtained using AlCrN/TiAlN-coated tools, when $V=160$m/min, $f=0.318$mm/rev and $d=0.3$mm.

This paper deals with the effect of machining parameters on tool wear, surface roughness and cutting forces in dry turning of low carbon steel with deep cryo-treated AISI D3 tool steel. AISI D3 tool steel was used for preparation of cutting tools as per International Standard Organization (ISO: 3685-1993). Deep cryogenic treatment ($-196^{\circ }$C) of D3 tool steel was carried out at different holding time (12h, 24h and 36h) followed by tempering at $150^{\circ }$C for 2h. Taguchi’s L27 orthogonal array is used for optimizing the process parameters during machining process. Analysis of variance (ANOVA) was carried out to study the significance of the input parameters. Mathematical models were developed using linear regression analysis for validating results. The tool worn surface shows the abrasion wear and oxidation wear were the main wear mechanisms observed under higher speed and feed rate cutting conditions.

Researchers are always trying to explore, use resources so that the machining performances become more efficient, economically viable, and environment-friendly which are in general, conflicting in nature. In this investigation, surface finish, material removal rate, and tool wear are considered as responses, and cutting speed, feed, and depth of cut are considered as input factors for optimization of AISI 4140 alloy steel during CNC dry turning. In most of the previous researches, weights of the responses are considered arbitrarily. But, in this investigation, weighted ratio analysis is considered as an optimizing tool whose weights are determined by the Eigenvectors obtained from the principal component analysis of the experimental data. This weighted ratio analysis technique requires very few computations compared to others, and even it can be performed without a computer. Surface texture of the tool wear is measured using image processing of the wear surface. First, a metallurgical microscope captures an image of the sharp tool (unworn), and RGB values of the gray scale image are noted, which acts as a reference. After machining, RGB values of the wear surface from the gray scale image are noted. Comparing these two RGB values, the amount of flank wear of the tool is determined. It is observed that the error is within 10% and therefore it is accepted.