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In the present work, an investigation has been made to study the effect of cutting parameters (speed, feed and depth of cut) on the multi-responses, Material Removal Rate (MRR) and Surface Roughness (Ra). The experiments were done on a conventional lathe using a tungsten carbide tool under dry environment. Twenty seven alternative combinations of speed, feed and depth of cut were considered (as per Taguchi’s standard L27 Orthogonal Array) for the machining of medium carbon steel EN8. For the optimization of multi-responses, the Multi-criteria decision making (MCDM) method, TOPSIS has been employed. Main effect plot for the Signal-to-Noise (S/N) ratios of the relative closeness coefficient (Ci+) was drawn using the MINITAB-16 software. From the TOPSIS and the main effect plot drawn for the relative closeness coefficient (Ci+), the optimal combination of the multi-responses were found at 27th alternative i.e. speed at 760 rpm, feed at 0.3 mm/rev and depth of cut at 1.5 mm respectively. The analysis of variance (ANOVA) has been done to know the influence of cutting parameters on the multi-responses. From the ANOVA results of the relative closeness coefficient (Ci+), it is found that the feed has high influence (F =41.08) followed by the depth of cut (F =25.78) and speed (F = 22.55).

Multi-criteria(or) attribute decision making (MCDM/MADM) methods have very high applications inindustriesforsolving real world engineering problems. In the present work, MCDM methods of Weighted summethod (WSM), Weighted ProductMethod (WPM) and TOPSIS, have been employed for the computational analysis of multi-responses. AA7075 has been taken as work piece for the experimentation and the experiments were done on CNC lathe as per the Taguchi’s standard L9 Orthogonal Array. The cutting parameters of speed, feed and depth of cut were taken as experimental inputs and Material Removal Rate (MRR) and Surface Roughness (Ra) were considered as responses. From the Weighted sum method (WSM) and Weighted ProductMethod (WPM) the optimal combination for multi-responses werefound at ninth alternative,i.e. speed: 2000 rpm, feed: 0.4 mm/rev and depth of cut: 0.75 mm. Similarly, from the TOPSIS results, the optimal combination for multi-responses werefound at seventh alternative,i.e. speed: 2000 rpm, feed: 0.2 mm/rev and depth of cut: 1 mm. Analysis of variance (ANOVA) has been done by using MINITAB-16 statistical software to find the influence of cutting parameters on the multi-responses. From the ANOVA results of WSM, WPM and relative closeness coefficient (Ci+), it is found that feed rate has high influence (For WSM, WPM and Ci+the F values are 60.50, 60.30 and 91.42 respectively) in affecting the multi-responses.

A Hybrid metal matrix composite (HMMCs) material has gained a lot of interest among industries due to its superiorproperties. Some of these properties are light in weight, high strength & rigidity, and high-temperature resistance. However,due to poor machinability, faster tool wear, machining of such materials exhibits greater challenges. The WEDM of aluminumbasedHMMC Al6010 (10% SiC and 15% Al2O3) is investigated. The input variable viz., pulse on time (Ton), pulse of time (Toff),peak current (I) and servo voltage (V) of the WEDM process was modelled using Response Surface Methodology (RSM). Theinvestigation was carried out through varying their effect on the material removal rate (MRR) and surface roughness (Ra). Using desirability analysis an attempt has been made to optimize the multiple responses simultaneously, the MRR and Ra wereoptimized for desirability and optimum result found as Ra = 1.58 μm and MRR = 18.31 mm3/min corresponding to V = 33.32volt, Ton = 117.45 μs, Toff = 45.041 μs and I = 219.70 A. In addition, the analysis of variance (ANOVA) is performed todetermine the significance of the selected input variable. It has been found that as peak current increases, MRR increases andRa decreases. The RSM model's validity and appropriateness are confirmed by the test results.

The Six Sigma practice is applied to increase the quality of the machined surface and in this work six sigma practice is usedto determine the optimal level of parameters. Six sigma technique is combine with Taguchi technique for optimizing theturning process parameters. Mild steel is used as a work piece to optimize the material removal rate. The primary objectiveof this research work is maximizing the material removal rate during turning of mild steel using single point cutting tool. Theturning process parameters considered in this work are cutting speed, feed rate and depth of cut. The optimal parameterscombination for signal to ratio values for turning process is A3-B4-C2, which gives cutting speed as 1000rpm, feed rate 0.20mm/rev and depth of cut 0.8mm. The validation experiments are also conducted and the optimal turning parameters areobserved to provide maximum material removal rate.

Silicon carbide (SiC) is used as a substrate material for power semiconductors; however, SiC chemical mechanical polishing (CMP) requires considerable time owing to its chemical stability and high hardness. Therefore, researchers are attempting to increase the material removal rate (MRR) of SiC CMP using various methods. Mixed-abrasive CMP (MAS CMP) is one method of increasing the material removal efficiency of CMP by mixing two or more particles. The aim of this research is to study the mathematical modeling of the MRR of MAS CMP of SiC with SiO2 and TiO2 particles. With a total particle concentration of 32 wt, using 80-nm SiO2particles and 25-nm TiO2 particles maximizes the MRR at 8 wt of the TiO2 particle concentration. In the case of 5 nm TiO2 particles, the MRR tends to increase with an increase in TiO2 concentration. In the case of particle size 10-25 nm TiO2, as the particle concentration increases, the MRR increases to a certain level and then decreases again. TiO2 particles of 25 nm or more continuously decreased MRR as the particle concentration increased. In the model proposed in this study, the MRR of MAS CMP of SiC increases linearly with changes in pressure and relative speed, which shows the same result as the Preston's equation. These results can contribute to the future design of MAS; however, the model needs to be verified and improved in future experiments.

This study investigates the characteristics of the sapphire wafer chemical mechanical polishing (CMP) process. The material removal rate is one of the most important factors since it has a significant impact on the production efficiency of a sapphire wafer. Some of the factors affecting the material removal rate include the pressure, platen speed and slurry. Among the factors affecting the CMP process, we analyzed the trends in the material removal rate and surface roughness, which are mechanical factors corresponding to both the pressure and platen speed, were analyzed. We also analyzed the increase in the material removal rate, which is proportional to the pressure and platen speed, using the Preston equation. In the experiment, after polishing a 4-inch sapphire wafer with increasing pressure and platen speed, we confirmed the material removal rate via thickness measurements. Further, surface roughness measurements of the sapphire wafer were performed using atomic force microscopy (AFM) equipment. Using the measurement results, we analyzed the trends in the surface roughness with the increase in material removal rate. In addition, the experimental results, confirmed that the material removal rate increases in proportion to the pressure and platen speed. However, the results showed no association between the material removal rate and surface roughness. The surface roughness after the CMP process showed a largely consistent trend. This study demonstrates the possibility to improve the production efficiency of sapphire wafer while maintaining stable quality via mechanical factors associated with the CMP process.

Abrasive fluidized bed machining (AFBM) is similar to general abrasive fluidized machining (AFM) in that it can perform polishing of the outer and inner surfaces of a 3-dimensional shape by the flow of particles. However, in the case of AFM, the shear force generated by the flow of the particles causes material removal, while in AFBM, the abrasive particles are suspended in the chamber to form a bed. AFBM can be used for deburring, polishing, edge contouring, shot peening, and cleaning of mechanical parts. Most studies on AFBM are limited to metals, and research on application of AFBM to plastic materials has not been performed yet. Therefore, in this study, we investigate the effect of rotating speed of the specimen and the air flow rate on the material removal characteristics during AFBM of polyacetal with a horizontal AFBM machine. The material removal rate (MRR) increases linearly with increase of the rotating speed of the main shaft because of the shear force between the particles of the fluidized bed and the rotation of the workpiece. The reduction in surface roughness tends to increase as the rotating speed of the main shaft increases. As the air flow rate increases, the MRR tends to decrease. At a flow rate of 70 L/min or more, the MRR remains almost constant. The reduction of the surface roughness of the specimen is found to decrease with increasing air flow rate.