Narrow Results

This investigation explores the application of electrical discharge machining (EDM) to ceramic composites constructed from Si₃N₄–TiN (Syalon 501) by testing both square and cylindrical electrodes. Various experimental methods have been employed, including design-of-experiments (DoE), Grey relational analysis (GRA), analysis of variance (ANOVA), confirmation testing, and scanning electron microscopy (SEM), in an effort to optimize machining settings and comprehend their effect on performance. While ANOVA revealed crucial parameter levels influencing overall machining conditions as measured by the grey relational grade (GRG), the sophisticated method of GRA considerably improved the machining characteristics. Significant improvements in the EDM process were shown experimentally, resulting in outstanding results for material removal rate (MRR), surface roughness (SR), and electrode wear rate (EWR). In particular, numerous benefits of the square electrode layout over the more common cylindrical arrangement stood out. All of the aforementioned resulted in an impressively high MRR (measured at 0.0281gm/min), a low EWR (at 0.0020gm/min), and a significant improvement in SR (at 0.3150$\mu$m). The GRG value was 0.0163 for the square electrode design, which was excellent, and 0.0025 for the cylindrical electrode, which was significantly better. The optimized parameters were successfully used, especially with the square electrode arrangement, leading to significant improvements in MRR and decreases in EWR. On the other hand, surface quality was negatively affected by larger parameter values, which increased the development of microfractures, particularly when using the square electrode design. In any case, our study provides strong proof that adjusted settings can greatly improve EDM performance, allowing for accurate machining of Si₃N₄–TiN composites with increased MRR, great surface texture, and reduced electrode wear. In conclusion, our study provides useful information to improve EDM procedures for Si₃N₄–TiN ceramic composites, as well as practical insights into increasing the efficiency and quality of EDM operations in a variety of industrial sectors.

In this research, stir casting was used to create the aluminium alloy (AA7075) composite filled with 10wt.% zirconia (ZrO₂) particles as reinforcement. Die sinking electric discharge machining (EDM) was used to examine the machining characteristics of the proposed composite. The machining experiments were executed in accordance with the $L_9$ orthogonal layout. Here, the material removal rate (MRR) and surface roughness (SR) were taken into account as the output responses, and the discharge current ($I_p$), pulse on-time ($T_{\mathrm{\text{on}}}$), and pulse off-time ($T_{\mathrm{\text{off}}}$) were taken as the machining parameters. To determine the optimal parameter conditions for the output responses, the technique for order preference by similarity to ideal solution (TOPSIS) approach was applied. According to the experimental findings, the optimum settings of the parameters are determined at 15amps of ‘$I_p$’, 750$\mu$s of ‘$T_{\mathrm{\text{on}}}$’ and 50$\mu$s of ‘$T_{\mathrm{\text{off}}}$’. ANOVA results stated that ‘$T_{\mathrm{\text{on}}}$’ has the most notable factor with a contribution of 90.85%. The interaction effect of parameters on the responses was shown by the contour plots. The confirmatory experiment was finally conducted at the optimum machining parameter settings, and it was found that the error only occurred in 8.4%.

Abrasive jet machining (AJM) process is commonly used for cutting and drilling of brittle materials in which the phenomenon of material removal can be considered as mechanical erosion by the impingement of high-velocity abrasives. The focus of this research is to compare the performance and economic benefits of recently developed hot abrasive jet machining (hot-AJM) with traditional AJM techniques when machining zirconia ceramic using silicon carbide (SiC) grain particles. The modified AJM employed abrasive air jet (combination of hot abrasive and compressed air) to strike on the work surface for material erosion. Briefly, the cutting performance is investigated by comparing the technological characteristics like material removal rate, machining cost, and taper angle of the developed hole. Abrasive grain size, nozzle pressure, and stand-off distance are considered as the variable factors for machining trials in accordance with the design of experiments. The usage of hot abrasives in AJM improved the material erosion owing to the occurrence of plastic deformation followed by deep chipping on the machined surfaces. From the results, it was observed that the hot-AJM outperformed the normal AJM with regard to improved material removal, reduced dimensional deviation of hole and minimal machining cost. According to the findings of the cost assessment, the machining of zirconia ceramic using hot-AJM was more cost-effective than using normal AJM since it resulted 25% reduction in the total cost of production. The overall machining cost expenditure per unit in hot-AJM was lower (INR 123.12) than expenditure in traditional AJM (INR 153.47). Machining with hot-modified AJM, compared to normal AJM, offers a more techno-economically viable solution for enhancing machinability.

This research aims to examine flank wear and material removal rates (MRRs) while finish hard turning work material of Inconel 718 with physical vapor deposition involving the process of cathodic arc evaporation TiAlN/TiCN-coated cermet CNC cutting tool insert. The L${}_{27}$Taguchi orthogonal design array is used for designing the experiments. The aim of this research is to optimize the process key parameters, such as cutting speed, rate of feed, depth of cut, and tool tip radius, in order to reduce flank wear and significantly improve MRR during the dry turning processes. This study examines the critical conditions of cutting parameters that were investigated by using analysis of variance (ANOVA), while the parameters which affect the flank wear and MRRs were optimized using response surface methodology according to the Design of the Taguchi orthogonal test. Mathematical models for both response parameters were derived using regression analysis, namely flank wear and MRR. The generated models achieved an accuracy of roughly 92% and 93% for estimating the flank wear and MRR values, respectively. The study revealed that cutting speed accounted for 34.28% of the most effective parameters in reducing flank wear, subsequently, the depth of cut reached 17.71%. In terms of MRR, the depth of cut accounted for 68.43% of the effectiveness, with a cutting speed of 12.94%. The optimal values for cutting speed, feed, cut depth and tool tip radius, in order to minimize wear, were determined to be 700m/min, 0.15mm/rev, 1.0mm, and 0.4mm, respectively. The optimal values for achieving the maximum MRR are 800m/min for cutting speed, 0.15m/min for rate feed, 2mm for cut depth, and 1.2mm for tool tip radius. Regression theory is used to construct correlation models, which have been shown to be statistically significant at the 0.05 level. An experimental approach is studied to investigate the coating defects and flaws of worn TiAlN/TiCN-coated cermet inserts using atomic force microscopy (AFM), optical and scanning electron microscope (SEM). Lastly, the creation of chips under optimal conditions has been shown.

A non-traditional machining method based on thermal energy, wire electrical discharge machining (WEDM) can precisely machine conductive materials. In addition to the cost of slot cuts, process parameters are important since they vary depending on the material properties. Hence, it is necessary to employ an appropriate technique to regulate the process parameters and ensure the desired quality of the slot cut. This study involved using WEDM to machine Inconel-825. The experiment used a Taguchi $L_9$ orthogonal array (OA) for maximum cutting rate and minimum surface roughness (SR). Peak current (I), spark on time ($P_{\mathrm{\text{on}}}$), and spark off time ($P_{\mathrm{\text{off}}}$), which are WEDM process parameters, were considered. Analysis of variance (ANOVA) and ANOM identified the significant contribution of cutting rate and SR in terms of WEDM parameters. A MOORA-PCA analysis was conducted to determine the optimum parameter settings. The OA results showed that the best values were at I (5A), $P_{\mathrm{\text{on}}}$ (50ms), and $P_{\mathrm{\text{off}}}$ (8ms), with an assessment value of 0.9935 and 1.0558 for linear and circular cut, respectively. The best outcomes from the MOORA-PCA optimization procedures were compared to the experimental outcome, and an improvement of 22.5643% and 17.7085% in linear and circular cuts were found, respectively. Optimizing WEDM parametrically utilizing a commercially available Inconel 825 machining technique based on MOORA-PCA MCDM is feasible.

This study deals about the influence of vibrations incorporated into a workpiece during powder-mixed electrical discharge machining (PMEDM) on quality measures such as material removal rate (MRR), surface roughness $(R_a)$ and microhardness. It has been found that the low-frequency vibration incorporated into the workpiece positively affects the processing efficiency of electrical discharge machining (EDM) and PMEDM. However, the effect of low-frequency vibration in PMEDM has been better than EDM. The higher vibration frequency significantly improves the MRR and $R_a$ in PMEDM. The MRR has been improved by 95.89% and with lower $R_a$ of 63.2% in PMEDM. The hardness of the machined surface after PMEDM using titanium powder mixed in dielectric liquid was increased approximately two times as compared with conventional EDM.

The purpose of this research paper is to present a new all-optical scheme to implement the logical behavior of generalized $n$th-order (2${}^n$:1) multiplexer logic. The proposed all-optical design is based on micro-ring resonator (MRR)-based all-optical switches and constructed by using “2${}^{n+1}$-2” MRR structures, arranged in a series “$n$” stage architecture. The presented configuration enjoys advantageous features like compact-sized systematic structure and ultra-fast speed. To validate the logical behavior of the proposed $n$th-order multiplexer, a second-order (2²:1) multiplexer is derived (from the proposed scheme) and discussed. Further, the usability of the presented all-optical multiplexer is demonstrated by developing an all-optical reconfigurable logic gate that can be reconfigured to perform various logic operations. To verify the logical behavior of MRR-based all-optical switch and presented all-optical multiplexer logic, numerical simulations through MATLAB software have been performed. The reported reconfigurable logic structure is also simulated in the MATLAB environment to validate the desired behavior.

Electrical discharge machining (EDM) is an unconventional machining process used for machining of hard-to-cut materials. Both EDM and micro-EDM processes are extensively used for producing dies and molds, complex cavities, and 3D structures. In recent years, researchers have intensively focused on improving the performance of both micro-EDM and EDM processes. This paper reviews the research work carried out by the researchers on vibration-assisted EDM, micro-EDM, and wire EDM. The consolidated review of this research work enables better understanding of the vibration-assisted EDM process. This study also discusses the influence of vibration parameters such as vibration frequency and amplitude on the material removal rate (MRR), electrode wear rate (EWR), and surface roughness (SR). The important issues and research gaps in the respective area of research are also presented in this paper.

The material removal rate (MRR) during precision finishing/polishing is a key factor, which dictates the process performance. Moreover, the MRR or wear rate is closely related to the material/part reliability. For nanoscale patterning and/or planarization on nano-order thickness coatings, the prediction and in-process monitoring of the MRR is necessary, because the process is not characterizable due to size effects and material property/process condition variations as a result of the coating/substrate interactions. The purpose of this research was to develop a practical methodology for the prediction and in-process monitoring of MRR during nanoscale finishing of coated surfaces. Using a specially designed magnetic abrasive finishing (MAF) and acoustic emission (AE) monitoring setup, experiments were carried out on indium-zinc-oxide (IZO) coated Pyrex glasses. After a given polishing time interval, AFM indentation was conducted for each workpiece sample to measure the adhesion force variations of the coating layers (IZO), which are directly related to the MRR changes. The force variation and AE monitoring data were compared to the MRR calculated form the surface measurement (Nanoview) results. The experimental results demonstrate strong correlations between AFM indentation and MRR measurement data. In addition, the monitored AE signals show sensitivity of the material structure variations of the coating layer, as the polishing progresses.

Machining of hard and brittle materials such as engineering ceramics, glass, and silicon is a formidable task. Unlike cutting processes employing plasma and lasers, better machining capabilities of abrasive jet machining are characterized by thermally damaged free surface which is highly competitive as well as important for survival of materials in service. In this paper, an attempt has been made to combine hot abrasives and compressed air to form a hot abrasive air jet. This study aims to analyze the cutting performance in hot-abrasive jet machining (HAJM) of hardstone quartz concerning surface roughness, taper angle (TA), and material removal rate (MRR). Combined approach of Box–Behnken design — analysis of variance, response surface methodology, and statistical technique (here desirability function approach), followed by computational approach (here genetic algorithm), is, respectively, employed for experimental investigation, predictive modeling, and multi-response optimization. Thereafter, the effectiveness of proposed two multi-objective optimization techniques is evaluated by confirmation test and subsequently, the best optimal solution (i.e. at air pressure of 7kgf/cm², abrasive temperature of $64^{\circ }$C, stand-off distance of 4 mm) is used for economic analysis. Result shows that the most significant parameter is abrasive temperature for surface roughness, whereas it is pressure in case of both TA and MRR. Applications of hot abrasives in AJM process have shown attention in enhancing the cutting performance for material removal. Due to lower percentage contribution of error (6.68% to Rz, 9.89% to TA, and 6.42% in case of MRR), a higher correlation coefficient ($R^2$) was obtained with the quadratic regression model, which showed values of 0.92, 0.9, and 0.93 for surface roughness, TA, and MRR, respectively.

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).

This work investigates the influence of tool surface area (TSA) on the average surface roughness ($R_a)$, tool wear rate (TWR) and material removal rate (MRR) in the micro-electrical discharge machining ($\mu$EDM). The effects of three different TSAs were investigated at three different discharge energy settings. It was observed that the TSA had substantial influence on $\mu$EDM performance owing to scaling effect. Therefore, the low-frequency workpiece vibration was applied to improve the $\mu$EDM performance. The surface topography of machined surfaces was examined using scanning electron microscopy to disclose the effect of TSA as well as vibration frequency on $\mu$EDMed surfaces.

In this paper, the copper (Cu)-based multi-wall carbon nanotube (MWCNT) composite tools were fabricated using electro-co-deposition method. The composite tools were prepared from different MWCNT concentrated (0.5, 0.75 and 1g/L) electrolytic solution and these tools were utilized in electro discharge machining (EDM). The experiments were performed with varying discharge currents. The results indicated that the incorporation of MWCNTs into the copper matrix greatly influenced the machining performances. A lower rate of tool wear and higher material removal rate (MRR) were observed for the copper-based MWCNT composite tools at different discharge currents. The highest tool wear rate (TWR) was reduced by 45.68% and the MRR was improved by 63% for the Cu-MWCNT (0.5g/L) composite tool compared to copper coated tool. At higher discharge current, smoother machined surfaces were generated using copper-based MWCNT composite tools compared to the copper tools. The SEM image exhibits that the micro-crack-free machined surfaces were produced by using copper-based MWCNT composite tools. The migration of tool material to the machined surface was also reduced for copper-based MWCNT composite tools.

Ni-based superalloys fall under the category of difficulty in machining type material owing to their poor thermal conductivity and high strength at extreme temperatures. Machining such materials using the traditional approach is a tremendously difficult task. On the other hand, EDM, one of the most sophisticated electro-thermal manufacturing processes, is used to machine such materials. It is a well-known non-traditional machining process for generating parts that require accuracy, have complex shapes, and are small in size. However, the use of EDM in Ni-based superalloys has some disadvantages like poor surface finish and low material removal rate. So, to alleviate these disadvantages, researchers introduced powder mixed dielectric fluid in the EDM process. Further, the performance of this technique has been enhanced by studying the effect of various nano/micro-size particles and their concentrations in the dielectric medium. In this paper, the authors have reviewed the impact of non-electrical and electrical process parameters on the output responses when machining Ni-based superalloys using powder mixed EDM. The challenges faced during the conventional machining of Ni-based superalloys and the mechanism proposed for powder mixed EDM, especially under the influence of suspended powders into the dielectric medium have also been presented in this paper. Finally, future research areas of powder mixed EDM of Ni-based Superalloys, such as (i) its modelling and simulation and (ii) the effect of tool motion and powder properties on its performance, are discussed in brief.

Shape memory alloys (SMAs) are an excellent material for producing components for a wide range of industrial applications, such as orthopedic implacers, micro-equipment, actuators, fittings, and screening components, as well as military equipment, aerospace components, bio-medical equipment, and fabrication requirements. Despite its remarkable qualities, the production of SMAs is a problem for investigators all over the globe. The purpose of this research is to evaluate the effects of altering the $T_{\mathrm{\text{on}}}$, $T_{\mathrm{\text{off}}}$, $I_{\mathrm{\text{p}}}$, and GV while processing copper-based SMA in an electrical discharge machining process on the material removal rate (MRR) and surface roughness (SR). The major runs were designed using a central composite design. SEM was also utilized to examine the micro-structure of EDM-processed electrode tools and work samples. SEM scans indicated the presence of debris, micro-cracks, craters, and a newly formed recast layer on the electrode tool and workpiece surface. High $I_{\mathrm{\text{p}}}$ and prolonged $T_{\mathrm{\text{on}}}$ provide huge spark energy simply at the work sample-tool contact, resulting in debris production. The experimental results reveal that the least and highest MRR values are 10.333 and 185.067mm³/min, respectively, while the minimum and maximum SR values are 3.07 and 7.15$\mu$m. The desirability technique, teacher learning based optimization (TLBO), and the Jaya algorithm were also utilized to optimize the studied solutions (i.e. MRR and SR) on a single and multi-objective basis. The best MRR and SR were determined using the desirability approach, the Jaya Algorithm, and the TLBO to be 152.788mm³/min and 4.764$\mu$m; 240.0256mm³/min and 1.637$\mu$m; and 240.0257mm³/min and 1.6367$\mu$m.

AISI P20 tool steel is commonly used for engineering of die holders, rails, plastic molds, wear strips, bolsters, shafts, and backers. When normally heated and sub-cooled, it experiences metallurgical modifications. Because the essential aspect of the “wire-electro discharge machine (WEDM)” is product finishing, this research examines the parametric responses when machining parent metal and sub-cooled metal (AISI P20). Thus, it is always necessary to choose a proper parametric arrangement for reaching maximum material removal rate (MRR), cutting speed with minimum surface roughness (SR), and kerf width. The effects of pulse on time, wire speed, discharge current, wire tension, and flushing pressure on individual machining reactions are also discussed in this study. An orthogonal array was created using Taguchi’s mixed experimental approach. The measurement alternatives and ranking according to compromise solution (MARCOS) method, the Honey Badger Algorithm, and the Taguchi-MARCOS method are engaged to obtain the important machining constraints and the optimal parametric settings for each response. When compared to the parent material, sub-cooled material has a greater cutting speed, SR, kerf breadth, and MRR. Here, cutting speed, MRR, and fitness were maximized along with minimization of SR and kerf width using the Honey Badger Algorithm as compared to both the MARCOS and Taguchi-MARCOS methods. According to ANOVA, for both parent and sub-cooled material, discharge current was the most significant and influential factor. The sub-cooled material’s machined surface contains smaller deposits and more spherical globules than the parent material, which has bigger melted deposits.

In this paper, experimental analysis was performed during micro-electrical discharge machining (micro-EDM) of titanium alloy Ti–6Al–4V (grade 5) using three types of tools viz. copper (Cu) tool, tungsten carbide (WC) tool, and synthetic graphite (Gr) grade three tool. The main process parameters were taken as (a) pulse on time ($T_{\mathrm{\text{on}}}$), (b) pulse off time ($T_{\mathrm{\text{off}}}$), (c) voltage (V), and (d) capacitance (C). The output responses were taken as the material removal rate (MRR) and tool wear rate (TWR). Taguchi method coupled with grey relational analysis (GRA) (L${}_{16}$ orthogonal array) technique was applied to optimize the input process parameters for both the responses. Scanning electron microscopy (SEM) analysis of the workpiece and tool was also performed to investigate the morphology of the machined surface and tool surface. Energy-dispersive spectroscopy (EDS) analysis was performed to investigate the elemental composition of the machined surface. The experimental finding reveals that tungsten carbide is the most suitable tool material for machining the chosen workpiece for obtaining optimal MRR and TWR. The optimum condition for the copper tool was found as 180V, 1000pf, 10$\mu$s ($T_{\mathrm{\text{on}}}$), and 10$\mu$s ($T_{\mathrm{\text{off}}}$). Meanwhile, the optimum parametric condition for tungsten carbide and graphite tools was found to be the same as 240V, 100pf, 20$\mu$s ($T_{\mathrm{\text{on}}}$), and 5$\mu$s ($T_{\mathrm{\text{off}}}$).

As the population of the world is continuously increasing, demand of the mechanical manufactured products is also increasing. Machining is the most important process in any mechanical manufacturing, and in machining two factors, i.e. material removal rate (MRR) and surface roughness (SR) are the most important responses. If the MRR is high, the product will get desired shape in minimum time so the production rate will be high, but we could not scarify with the surface finishing also because in close tolerance limit parts like in automobile industry, if the surface is rough exact fit cannot take place.

The term optimization is intensively related to the field of quality engineering. Abrasive water jet machining is an important unconventional machining, in order to obtain better response, i.e. material removal rate and surface roughness. Various process parameters of AWJM need to be observed and selected to improve machining characteristics. Better machining characteristics can be achieved by optimizing various process parameters of AWJM.

This study considers four process control parameters such as transverse speed, standoff distance, abrasive flow rate and water pressure. The response is taken to be material removal rate and surface roughness. The work piece for stainless steel AISI 304 material of size 15 cm × 10 cm × 2 cm is selected for experiments. Sixteen experimental runs (two trials for each experimental runs) were carried out for calculating MRR and SR and average value of these two trials have been taken for analysis. MRR is normalized according to higher-is-better and SR is normalized according to lower is better. The experiment data analysis is done and VIKOR index is found. Finally, the analysis of VIKOR index using S/N ratio is done and found the most significant factor for AWJM and predicted optimal parameters setting for higher material removal rate and lower surface roughness. Verification of the improvement in quality characteristics has been made through confirmation test with the predicted optimal parameters setting. It is found that the determined optimum combination of AWJM parameters gives the lowest VIKOR INDEX which shows the successful implementation of VIKOR Method coupled with S/N ratio in AWJM.

Intermetallic/ceramic composites with multiple responses are based on L₁₈ orthogonal array with gray relational analysis (GRA). This paper presents a new approach for the optimization of drilling parameters on drilling MoSi₂–SiC composites. Optimal machining parameters can then be determined by the gray relational grade as the performance index. In this study, the sparking parameters namely current (I), pulse on time (t_on), pulse off time (t_off), spark gap and dielectric flushing pressure (P) are optimized with considerations of multiple performance characteristics including multi responses such as material removal rate (MRR), electrode wear rate (EWR), circularity (CIR), cylindricity (CYL), perpendicularity (PER). A gray relational grade obtained from the GRA is used to solve the electrical discharge machining (EDM) process with the multiple performance characteristics. Based on the gray relational grade, optimum levels of parameters have been identified and significant contribution of parameters is determined by ANOVA. Confirmation test is conducted to validate the test result. Experimental results have shown that the responses in EDM drilling process can be improved effectively through the new approach.

In the present study, aluminum alloy (Al/3.25Cu/8.5Si) composites reinforced with fly ash particles was fabricated using stir casting technique. Fly ash particles of three different size ranges 53–75, 75–103 and 103–125$\mu$m of 3, 6 and 9 weight percentages was reinforced in aluminum alloy. The effect of peak current, pulse on time, and pulse off time on surface roughness (SR), material removal rate (MRR) and tool wear rate (TWR) of electric discharge machining (EDM) was investigated. A central composite design using response surface methodology (RSM) was selected for conducting experiments, and mathematical models were developed using Design Expert V7.0.0 software. Analysis of variance (ANOVA) technique was used to check the significance of the models developed. Peak current was the major factor influencing the EDM of aluminum fly ash composites. The MRR, TWR, and SR of aluminum fly ash composites were also influenced by the size of the fly ash particles.