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In the fabrication of parts in auto and aero segments, the use of ceramic (SiCp, Al2O3p) reinforces aluminum alloy found to be increased than that of steel and cast iron. This matrix-reinforced alloy has a high strength to weight ratio along with higher modulus and hardness, the lower thermal coefficient of expansion, and improved tribological properties. To this extent, this paper investigates the turning characteristics and optimization study of newly developed metal matrix composites by the addition of both hard ceramic SiCp and soft stable lubricant molybdenum disulfide (MoS2p). The samples such as Sample 1: AlSi10Mg/3SiCp, Sample 2: AlSi10Mg/2MoS2p and Sample 3: AlSi10Mg/3SiCp /2MoS2p are prepared using the automated stir-casting machine. The particles are observed to be uniformly distributed in the composite. After density and hardness measurement, the samples are subjected to machining, and the responses are optimized by using response surface method.

In the present paper, to predict the process relation between laser-assisted machining parameters and machinability characteristics, statistical models are formulated by employing surface response methodology along with artificial neural network. Machining parameters such as speed of cut; the rate of feed; along with the power of laser are taken as model input variables. For developing confidence limit in collected raw experimental data, the full factorial experimental design was applied to cutting force; surface roughness; along with flank wear. Response surface method (RSM) with the least square method is used to develop the theoretical equation. Furthermore, artificial neural network method has been done to model the laser-assisted machining process. Then, both the models (RSM and ANN) are compared for accuracy regarding root mean square error (RMSE); model predicted error (MPE) along with the coefficient of determination (R2).

In recent years, aluminum metal matrix composites (Al-MMC) are found as a potential material for numerous applications owing to its excellent tribological and mechanical properties. In this work, the machining characteristics of aluminum alloy (Al7075) reinforced with TiC/MoS2 having nanoparticle has been studied. The samples of aluminum metal matrix composites by varying TiC in 0, 2 and 4 and MoS2 in 0 and 2 of the percentage weight of aluminum alloy (Composite 1(Al7075), Composite 2 (Al7075/2TiC/2MoS2) and composite 3 (Al7075/4TiC/2MoS2), respectively) are fabricated by the stir-casing method. The turning characteristics of the developed metal matrix composites are studied at various parameters such as cutting velocity (30 m/min, 60 m/min and 90 m/min), cutting depth (0.5 mm, 1.0 mm and 1.5 mm) and composites (1, 2 and 3) using TiN coated cutting tool by dry turning at 0.05 mm/rev feed rate.

Nickel based materials of Nimonic C-263 and Waspaloy are used nowadays for aerospace applications owing to its superior strength properties that are maintained at a higher temperature. Tool wear and cutting temperature in the vicinity of cutting edge are two essential machinability characteristics for any cutting tool. In this regard, this study is pursued to examine the influence of factors on measuring of tool wear (Vba) and cutting temperature (Ts) during dry machining of two alloys studied experimentally based on Taguchi method and response surface methodology. Taguchi’s L16 orthogonal array is used to design the experiment and a PVD (TiAlN), CVD (TiN/Al2O3/TiCN) coated carbide inserts are used on turning of two alloys. The factor effect on output responses are studied using analysis of variance, empirical models, and responses surface 3D plots. To minimize the response and to convert into one single optimum level, responses surface desirability function approach is applied.

Composites materials are substituting constituents for traditional materials due to their remarkable properties, and the addition of nanoparticles gives a new development in the material domain. The nanoparticles influence on fabrication and machinability investigation study is essential as the composites to be used in applications like automotive and aerospace. The current study investigates the machinability characteristics of Al2219 based metal composites reinforced with nanoparticles of SiN/MoS2. Al2219- reinforcements (SiN and MoS2) composites are fabricated by the method of stir casting. Four different compositions (Al2219/SiN (2 wt% and 4 wt%), , Al2219/2 wt.% SiN/ 2 wt.% MoS2, Al2219/2 wt.% MoS2) are fabricated by varying the different weight percentages of nanoparticles reinforcements. An attempt is made to study the investigation analysis of force, surface roughness, and tool wear using CNC machine lathe to consider the effect of cutting speed, cutting depth, and samples.

This paper presents the parametric study, process benefits, optimization and chip appearance of machining parameters on turning of the Inconel 718 using Nd: YAG laser source. To analyze the mentioned above effect on alloy 718, the cutting inserts of chemical vapor disposition coated (CVD) TiN/TICN/Al2O3 are used to turn at the time of machining. To evaluate the linear (mean effect plots) and interaction effect (3D surface plots) of laser parameters on the force, roughness and tool wear to keep the minimal, experiments of the L27 orthogonal array are done by selecting the controllable parameters viz speed, the rate of feed along with laser power. From the parametric study, increase in speed and laser power along with decrement in the rate of feed resulted in lower cutting force. But surface finish and tool wear reduced with a decline in speed and scale of feed and increased with increment in laser power.