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The demand for high-performance materials in aerospace, automotive, and power generation industries has led to the development and utilization of advanced superalloys. Nimonic C-263/263, a nickel-based superalloy, is widely employed in critical components of jet engines, such as combustion chambers, heat exchangers, reformer tubes, gas turbine power generation components like turbine discs, shafts, and blades, due to its exceptional high-temperature strength, corrosion resistance, and creep properties. However, the inherent hardness and toughness of this alloy pose significant challenges for conventional machining processes. Abrasive waterjet cutting (AWJC) emerges as a promising alternative for the efficient machining of such difficult-to-cut superalloy materials. This paper presents an in-depth investigation on the machinability of thick Nimonic 263 superalloy plate material using AWJC, aiming to provide insights into the effects of process parameters, cutting performances, and resulting surface integrity due to change in declination angle measurement. An examination was also conducted on the pattern of striation formation under varying process parameters, utilizing digital microscopic images. The goal of the study is to establish a link between the parameters of striation production and the angle of jet impingement. The results indicate that a decrease in striation during the water jet processing of Nimonic 263 superalloy is caused by an increase in the declination angle.

The machinability of aluminum alloy (Al-6082) has the scope of enhancement by integrating Friction Stir Processing (FSP) with tool geometry, tool shape and different tool materials. In this research, the role of tool pin shape has been studied by experimenting on various tool shapes (square, hexagonal and octagonal) with the aim of machinability improvement. In FSP, the tool rotation speed is 930rpm and tool travel speed is 26mm/min. The specimens have undergone tensile, microhardness and microstructure testing using optical microscope and scanning electron microscopy. The percentage elongation has been increased from 15% to 29% in the case of the octagonal-shaped tool pin; similarly, the (Vickers’) microhardness value is 14.6% higher than the square- and hexagonal-shaped tool pins. Among these tool pin shapes, the octagonal-shaped tool pin succeeded in providing the best-in-class machinability performance on Al-6082 T6 alloy with FSP. It may unveil the newer scopes of FSP on Al-6082 for automotive components assembly and other similar applications.

The growing need to machine challenging materials, especially nickel-based superalloys found in vital aerospace and automotive parts, is evident. This study examines the machining of 15.5 mm Nimonic-263 superalloy using Abrasive Waterjet Machining (AWJM). Nine trial sets, repeated thrice, are comprehensively evaluated using an L9 orthogonal array design to analyze crucial machining variables: the impact of Stand-off Distance, Waterjet Pressure, and Traverse Speed on Kerf Angle, Machining Time, and Material Removal Rate. Statistical significance is evaluated through multi-parametric analysis of variance, and quadratic multiple linear regression models are formulated to correlate output responses with machining variables. The JAYA optimization algorithm is introduced to optimize the machining process, aiming to minimize Kerf Angle and Machining Time while maximizing Material Removal Rate. A comparison with Ant-Lion, Genetic, and Multi-Verse Optimization algorithms highlights JAYA’s effectiveness. A confirmation test validates the JAYA algorithm’s output, confirming its superior performance. This research aids in optimizing machining parameters for challenging materials, benefiting critical components in various industries, especially aerospace.

This paper investigates the impact of high-speed machining with heat-assisted machining (HAM) on the machinability of heat-treated SKD61 steel, utilizing alloy cutting tools. The study encompasses microstructure analysis, mechanical properties evaluation, chip color examination, surface roughness assessment and cutting force measurement during the machining process. Experiments are conducted under controlled conditions with advanced equipment. Findings indicate that at 200°C and 350°C, SKD61 steel’s microstructure remains unchanged, while at 500°C, there’s a superficial alteration of approximately 0.05mm thickness. Material hardness remains consistent across temperatures. Unique chip color variations serve as temperature indicators. Cutting force consistently decreases with rising temperature, highlighting the intricate relationship between temperature, material behavior and cutting mechanics. Surface roughness improves with higher temperatures, emphasizing the potential benefits of HAM in precision manufacturing.

Research on machining continues increasingly today. The effects of independent variables (cutting speed, feed rate, cutting depth) on dependent variables (material removal rate (MRR), average surface roughness (Ra), sound intensity, energy consumption, and vibration) are among the most researched topics in machining. It is also important to achieve optimum results with low cost and time savings in machining.

In this study, titanium alloy TC4 material was turned on CNC lathe. Taguchi L${}_{16}$ mixed level design was used in experimental design. MRR, Ra, sound intensity, energy consumption, and vibration values were measured for the determined cutting parameters. The measured values were researched experimentally and statistically. Effective parameters were determined. It was concluded that the cutting parameter that has the greatest effect on MRR, Ra, energy consumption, and vibration is the feed rate. In addition, the depth of cut was the parameter that most affected the sound intensity. Control experiments were carried out after determining the optimum machining parameters. With multiple optimization, the predictions were made with approximately 89% accuracy (92.75% for MRR, 92.49% for Ra, 89.45% for sound intensity, 92.70% for energy consumption, 96.16% for vibration).

Equal channel angular pressing (ECAP) processed materials have higher grain refinement and strength, and they exhibit more surface roughness when they are machined. This enhancement in the properties highly influences the surface roughness and material removal rate of the materials. The commercial pure aluminum has a wide variety of applications when it is enhanced with high strength properties. In this paper, the machinability of commercially pure aluminum processed through ECAP is investigated in turning operations. Different ECAP processes are carried out to study the microstructural characterization and mechanical properties of the material. The material removal rate and surface roughness are tested by performing the turning operation in the CNC lathe with chemical vapor deposited carbide tool such that the feed rate, spindle speed and depth of cut are considered as the machining variables. To create a hypothesis for the experimentation, the empirical models are developed for the objective functions using the statistical technique response surface methodology (RSM) such that the response models are the objective functions and the model variables are the machining parameters. The response models are verified for the adequacy through ANOVA and $p$-test, and also verified for the closeness with the experimental results. Artificial neural network (ANN)-based empirical equations are also developed for the objective functions using the RSM design matrix and the results of both the RSM and ANN are compared for the suitability.

This research focuses on wrought Ti-6Al-4V machining using coated carbide inserts under flood cooling to study the machinability characteristics. Machining parameters are optimized, and mathematical models are developed for correlations. Surface roughness lies between 0.215$\mu$m and 0.830$\mu$m and even below 1$\mu$m during machining. Flank wear lies within 0.033–0.16mm which is below the 0.2mm criteria of wear. Cutting temperature lies between 31^∘C and 158^∘C. The reduction of cutting temperature and chip serration under flood cooling and the subsequent transfer of heat from the shear zones help to generate good surface finish and may be due to the evolution of a lower wear rate. Abrasion, chipping, adhesion and built-up-edge are seen as major mechanisms of wear. The optimal conditions are found to be a depth of cut of 0.1mm, 0.1mm/rev feed rate and 70m/min cutting speed. There is an improvement in results at optimal conditions of 38.42% for Ra, 60.86% for VBc and 27% for $T$, respectively, than initial parametric conditions. Further, grey relational grade has been improved by 0.263. Machinability models developed through quadratic regression are observed to be significant.

In this study, metal matrix composite (MMC) materials were made with an aluminum matrix (AA7075 alloy) and reinforcement silicon carbide (SiC) elements using molten metal stir and indirect squeeze casting. SiC was used as a reinforcing element in the making of MMC material in different amounts (10%, 14%, and 18%) by mass. Electro Discharge Machining (EDM), cut depth (0.5 mm), three different pulse-on times, three different discharge current values, and a fixed pulse-off time (20 s) were used to machine MMC materials. The effects of machining parameters on machining time, average surface roughness, hole diameter, and material wear difference after machining were studied. As a result of the study, the composite material with 75 $\mu$s pulse-on time, 6A current value, and 10% reinforcement element had the lowest machining time, the largest hole diameter, and the smoothest average surface. These machining parameters and materials also had the shortest machining time (5 min). Based on the signal-to-noise ratios, the best parameters for average surface roughness, hole diameter, Processing time, and material wear amount (MMC, discharge current value, and impact time) were found to be $L_2{L}_1{L}_1$, $L_3{L}_1{L}_1$, $L_1{L}_3{L}_3$, and $L_1{L}_1{L}_2$, respectively. Based on the ANOVA results, the $R$² values for the average surface roughness, hole diameter, machining time, and material wear loss value were 99.3%, 98.7%, 77.8%, and 97.3%, respectively.

In today’s rapidly evolving manufacturing industry, researchers and engineers are constantly seeking innovative methods to improve machining processes. One such area of interest is the use of electrical discharge machining (EDM) for difficult-to-machine metals like SS316. This research compares the performance and economic aspects of traditional EDM and powder-mixed EDM when machining SS316 using copper electrode. Graphite powder dispersed in biodegradable palm oil is investigated as a dielectric media with the aim of enhancing EDM performance. According to the findings, the analysis of the cutting performance of different machinability aspects revealed that using graphite powder mixed with palm oil as a dielectric in EDM outperformed conventional EDM relating to material removal, surface finish, surface hardness, electrode wear rate and hole overcut. The flushing condition and unique properties of graphite powder and palm oil, such as cooling, and thermal conductivity, contributed to the improved performance observed in EDM processes. These findings highlight the potential of graphite powder mixed with palm oil as a promising alternative dielectric in EDM, offering enhanced machining capabilities and improved surface quality. The total machining expenditure per part under PMEDM (INR 505.50) is lowered by 9.2% than expenditure under conventional EDM (INR 525). The surface microhardness of the machined component attained using graphite powder-mixed EDM is enhanced in comparison to that achieved using standard EDM due to the creation of a carbon-rich re-solidified layer.

The present study addresses the machinability investigation in finish dry hard turning of high strength low alloy steel with coated ceramic tool by considering cutting speed, feed and depth of cut as machining parameters. The technological parameters like surface roughness, flank wear, chip morphology and economical feasibility have been considered to investigate the machinability performances. Twenty seven set of trials according to full factorial design of experiments are performed and analysis of variance, multiple regression method, Taguchi method, desirability function approach and finally Gilbert’s approach are subsequently applied for parametric influence study, mathematical modeling, multi-response optimization, tool life estimation and economic analysis. Results indicated that feed and cutting speed are the most significant controlled as well as dominant factors for hard turning operation if the minimization of the machined surface roughness and tool flank wear is considered. Abrasions, adhesion followed by plastic deformation have been observed to be the principal wear mechanism for tool life estimation and observed tool life for coated ceramic insert is 47min under optimum cutting conditions. The total machining cost per part is ensued to be lower ($0.29 only) as a consequence of higher tool life, reduction in downtime and enhancement in savings, which finds economical benefits in hard turning. The current work demonstrates the substitution of conventional, expensive and slow cylindrical grinding process, and proposes the most expensive CBN tool alternative using coated ceramic tools in hard turning process considering techno-economical and ecological aspects.

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.