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Polymer composites are extensively accepted in the material fraternity due to their lightweight, high-strength quality. The carbon nanomaterials (CMNs) significantly enhance the thermal resistivity, anti-corrosion, mechanical, and physical features of polymer (epoxy) composites. This paper emphasizes the machining aspects of Zero-dimensional Carbon nano onion (0D-CNO) reinforced polymer composites. The influence of four varying constraints, namely, weight% of CNO, Spindle speed, feed rate, and depth of cut, was examined through the Grey integrated JAYA algorithm (GRA- JAYA). The desired value of Surface roughness (Ra) and Material Removal Rate (MRR) was controlled through process constraints. The Milling experimentation was executed through the Taguchi L27 orthogonal array (OA). The conflicting machining performances were aggregated by Grey theory to develop the algorithm fitness function. To obtain a better work efficiency, higher spindle speed, feed rate, depth of cut, and lower weight% of nanomaterial addition are proposed in this study. Hence, the result demonstrated that the weight% of CNO reinforcement and feed rate are the most influential factors for optimal machining performance results. The finding of the proposed module has compared with other metaheuristics algorithms, which demonstrate the higher application potential to acquire the desired machining characteristics. It can be suggested for the enhancement of quality and productivity indices of the polymer manufacturing sector. [ABSTRACT FROM AUTHOR]

One of the most former and widely utilized unconventional machining is known as the process of electric discharge machining (EDM). This is a procedure, where a serialized set of electric discharges are applied to eliminate the material from a workpiece (i.e., electrically conductive). This article proposes a bi-objective optimization of process arguments in machining of stainless steel of 630 (SS630) grade using both experimentation and thermal investigation. Here, flushing pressure ( P F ), pulse on-time ( T ON ), peak current ( I p ), and pulse off-time ( T OFF ) are assumed as the input process parameters to conduct a series of experiments on die-sinking EDM (DS-EDM) of SS630 to predict the output characteristics of machining optimization using grey relation analysis (GRA). Both material removal rate (MRR) and surface roughness (SR) are used for evaluating the output response obtained using the machining performance. In addition, thermal investigation is performed using finite element method (FEM) analysis to compute theoretical MRR (T-MRR) for the distribution of temperature on workpiece. Further, GRA is employed to obtain the optimal process parameter combination for best output responses. From the confirmation test results, the optimal combination obtained using GRA approach is at I p = 6 A , T ON = 35 μ s , T OFF = 90 μ s , and P F = 4 MPa. [ABSTRACT FROM AUTHOR]

Ti6Al4V plays a prominent role in manufacturing component production due to tremendous mechanical and engineering properties. The present investigation focuses on the impact of machining input constraints and the advancement of robust optimisation technique during powder-mixed wire electric discharge machining (PMWEDM) of Ti6Al4V alloy. The machining inputs are figured out for experimentation such as pulse on time (Ton), pulse off time (Toff), peak current (Ip), gap voltage (GV), and powder concentration (PC) based on preliminary observation and existing research work on that area. Another attention is to reach the optimal value of the metal removal rate, surface roughness, and cutting speed. A comparative study is executed between GRA and GRA-PCA in the present research work. It is found that GRA-PCA has an adequate capability of 23.04% larger than the GRA technique. ANOVA analysis is revealed that powder concentration and pulse on time are the most significant parameter whereas pulse off time and gap voltage are the significant parameter for surface roughness. Therefore, the confirmation test is validated through experimentation and surface topography analysis. [ABSTRACT FROM AUTHOR]

The use of multiwall carbon nanotube (MWCNT) reinforced polymer nanocomposites have significant importance since MWCNT enhances the aspect ratio and interface conditions of polymer materials. However, the machining aspects of carbon nanofillers are still a potential area of research. The mechanical and electrical properties of MWCNT/epoxy nanocomposites makes it a suitable alternative to conventional engineering materials. This work focused the machining characteristics optimization during drilling of MWCNT/epoxy nanocomposites using TOPSIS and GRA theory. The machining characteristics are considered which are surface roughness, torques and thrust. By using both the multi-criteria optimization techniques, all the machining characteristics aggregated into the single objective function. The effects of drilling parameters have been investigated by variance analysis. The outcomes of both the proposed module give different optimal conditions of process parameters. The confirmatory experiment carried out to validate the obtained results, and it has been observed that GRA is more feasible than TOPSIS. During machining, the cutting force rises with the high feed rate, and the lower value of feed rate reduces the surface roughness. The achieved improvements in drilling performances are highly required for an efficient machining environment. Further, a microstructural investigation was done to check the quality of the machined samples. [ABSTRACT FROM AUTHOR]

Superalloys are typical "difficult to machine" materials, which could be processed by electrical discharge machining (EDM). The studies about the machining performance of superalloys mainly concentrate on nickel-based superalloys and titanium superalloys. But for iron-based superalloys, such as GH2132, which has an extensive application in numerous fields, the investigations are seldom conducted. A high energy die-sinking EDM is proposed in this paper, and the deionized water is used as the dielectric. The machining performance of GH2132 through the proposed machining method is systemically investigated. Taguchi L25 orthogonal array (L25) is utilized to investigate the influences of machining parameters (peak current (I), pulse on time (Ton), and pulse off time (Toff)) on output indexes (material removal rate (MRR), relative electrode wear rate (REWR), and diameter overcut (DOC)). Single-objective optimization is performed to acquire maximum MRR, minimum REWR, and DOC by analysis of variance (ANOVA). The optimal machining performance, which is better than the results from L25, is also obtained by gray relation analysis (GRA) and multi-objective optimization. [ABSTRACT FROM AUTHOR]

This work is motivated by environmentally conscious machining and focus on the basic properties and applicability of nano cutting fluids in machining. Cutting fluids are formulated by dispersing carbon nanotubes (CNT) in coconut oil (CC) with varying percentage of nanoparticle inclusions (NPI). The properties such as density, heat transfer coefficient, dynamic viscosity and thermal conductivity are determined before their application. The formulated nanofluids are applied during machining through minimum quantity lubrication (MQL) technique. Microbial contamination and biodegradability tests are conducted to assess the quality of nanocutting fluids. Viscosity is found to decrease with increase in temperature where, as specific heat slightly decreased with an increase in NPI for CNT dispersed fluids. It is observed that nanofluids in MQL upshot in the reduction of cutting force, cutting temperature, tool wear and surface roughness. CNT dispersed cutting fluids at 0.5% NPI and speed of 60 m/min, 0.131 mm/rev feed and 0.5 mm depth of cut (DOC) shown better performance in the selected range of parameters. Machining performance is more influenced by the percentage of nanoparticles and then the depth of cut, speed and feed respectively. For the cutting conditions, the influence of DOC in obtaining minimum cutting forces and reducing cutting temperatures is found to be 85% and 45% respectively for nBA dispersed fluids. The extent of influence of %NPI is found to be 35.19% for CNT dispersed fluids to obtain reduced cutting forces, cutting temperatures, tool wear and surface roughness according to GRA analysis. Microbial contamination is observed to be the least for 0.5% NPI dispersed fluids. It is also identified that nano cutting fluids used in this work are biodegradable and biologically treatable for disposal as well. [ABSTRACT FROM AUTHOR]

• The drilling has been performed on MWCNT epoxy nanocomposites using RSM design. • PCA was used for weight assignment of surface roughness, torque and thrust force. • Comparison of GRA and GRA-PCA module was performed to check the feasibility. • Process parameter taken as MWCNT wt%, spindle speed, feed rate and Tool materials. • The confirmatory experiment shows the desired improvement in machining responses. Epoxy nanocomposites play a leading role in manufacturing sectors due to excellent engineering properties. This paper highlights the influence of process constraints and the development of a robust optimization approach during drilling of Multiwall carbon nanotube/Epoxy Nanocomposites. The parameters considered are MWCNT % (W), Drill bit speed (N), feed rate (F), and Drill Bit (M) Materials (HSS, Carbide, TiAlN) based on pilot experiments performed and existing literature. The unified aim is to achieve the best machining performances, i.e., Surface roughness, Torque, and Thrust force. The optimal setting was found as W-1.0%, N-1000 rpm, F-50 mm/min with TiAlN drill bit. A comparative study between GRA and GRA-PCA hybrid modules has been performed to check the application potential, which shows that Hybrid GRA-PCA is more capable than traditional GRA in terms of less average error (5.037%) and overall improvement of 13.99% in assessment values. [ABSTRACT FROM AUTHOR]