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The purpose of this paper is to investigate the optimized setting of wire-cut electrical discharge machining (WEDM) parameters at which material removal rate (MRR) and mean roughness depth (Rz) set a compromise. The problem in the processing of Ti-6Al-4V by conventional processes is a high strength, high hardness, high tool wear. Due to which WEDM is adopted to machine Ti-6Al-4V biomedical alloy. Ti-6Al-4V alloy has a number of applications in the engineering and medical industries due to its high strength biocompatibility.

The effect of control factors (i.e. pulse on-time: Pon; pulse off-time: Poff; servo voltage: SV) on the MRR and Rz is investigated in the present research. The planning of experiments is done using a Taguchi-based L9 orthogonal array. The percentage influence of each factor on responses is also evaluated. The multi-objective optimization is done using the grey approach initially. After that, the results were also calculated using harmony search (HS). Therefore, a hybrid approach of grey and HS is used to find the optimized values of MRR and Rz.

The maximum value of grade calculated by grey-HS is 0.7879, while in the case of the experimental run the maximum value of grey grade is 0.7239. The optimized setting after improvisation at this grade value is Pon: 130 µs; Poff: 45 µs and SV: 70 V for MRR and Rz collectively. The validation of the suggested setting is completed by experimentation. The values of MRR and Rz are coming out to be 6.4 mm³/min and 13.84 µm, which represents improvised results after the implementation of the HS algorithm.

The integration of the grey approach with the HS principle in the manufacturing domain is yet to be explored. Therefore, in the present research hybrid approach of grey-HS is implemented in the manufacturing domain having applications in medical industries.

In many of today’s manufacturing industries, such as automobile, aerospace, defence, die and mould making, medical and electrical discharge machining (EDM) has emerged as an effective material removal process. In this process, a series of discontinuous electric discharges is used for removing material from the workpiece in the form of craters generating a replica of the tool into the workpiece in a dielectric environment. Appropriate selection of the tool electrode material and combination of input parameters is an important requirement for performance enhancement of an EDM process. This paper aims to optimize an EDM process using single-valued neutrosophic grey relational analysis using Cu-multi-walled carbon nanotube (Cu-MWCNT) composite tool electrode.

This paper proposes the application of grey relational analysis (GRA) in a single-valued neutrosophic fuzzy environment to identify the optimal parametric intermix of an EDM process while considering Cu-MWCNT composite as the tool electrode material. Based on Taguchi’s L9 orthogonal array, nine experiments are conducted at varying combinations of four EDM parameters, i.e. pulse-on time, duty factor, discharge current and gap voltage, with subsequent measurement of two responses, i.e. material removal rate (MRR) and tool wear rate (TWR). The electrodeposition process is used to fabricate the Cu-MWCNT composite tool.

It is noticed that both the responses would be simultaneously optimized at higher levels of pulse-on time (38 µs) and duty factor (8), moderate level of discharge current (5 A) and lower level of gap voltage (30 V). During bi-objective optimization (maximization of MRR and minimization of TWR) of the said EDM process, the achieved values of MRR and TWR are 243.74 mm³/min and 0.001034 g/min, respectively.

Keeping in mind the type of response under consideration, their measured values for each of the EDM experiments are expressed in terms of linguistic variables which are subsequently converted into single-valued neutrosophic numbers. Integration of GRA with single-valued neutrosophic sets would help in optimizing the said EDM process with the Cu-MWCNT composite tool while simultaneously considering truth-membership, indeterminacy membership and falsity-membership degrees in a human-centric uncertain decision-making environment.

This study aims to explore the machinability of ZrB₂ using electrical discharge machining (EDM) with different tool materials.

The workpiece for this study was fabricated through powder metallurgy compaction method. The disc is machined using diamond load grinding to have parallel surfaces, then, 2 mm diameter holes are machined on the disc using EDM spark erosion machine with different tool materials (graphite, aluminium, tantalum, niobium, copper, brass, silver, tungsten and titanium). Roundness, geometry of hole, and diameter of the hole at different diametric planes, surface roughness (SR), material removal rate (MRR), tool wear rate (TWR), taper angle and recast layer (RCL) thickness are measured. The photographic analysis of tools, holes in the top view, bottom view and sectional view. SEM analysis was conducted to study the recast layer. Desirability function analysis was employed to rate the performances of tools.

A new theory is developed which relates recast layer thickness with melting point and thermal conductivity of the tool materials. Machining of ZrB₂ by EDM is feasible; graphite is identified as the best tool. Recast layer thickness of the machined surfaces are indirectly proportional to the product of melting point and thermal conductivity of tool. Ablation behaviour of ceramic workpiece lead additional material losses in the tool.

Extremely high strength and hardness of ZrB₂ due to the coexistence of strong covalent and metallic bond make mechanical machining very difficult or even impossible. No machinability studies were conducted previously on ZrB₂ using EDM; this work reveals machinability study of ZrB₂ with different tool materials.

The purpose of the study is to machine the composites at lower machining time with higher accuracy without causing delamination.

Abrasive jet machining is the technology appropriate for machining composite materials to obtain good dimensional accuracy without causing de-lamination. The central composite design was followed in deciding the number of experiments to be carried out.

The influence of abrasive jet machining process parameters on machining time, material removal rate (MRR) and kerf characteristics were investigated. The experimental results proved the newly designed internal threaded nozzle increased MRR, thereby reducing the machining time.

Machining of glass fibre reinforced polymer (GFRP) is one of the challenging tasks given its non-linear and in-homogeneous properties. In this investigation, newly developed threaded and unthreaded nozzles in machining were used for making holes on the GFRP composites.

Lapping is a vital flattening process to improve the quality of processed semiconductor wafers such as single-crystal sapphire wafers. This study aims to optimise the lapping process of the fixed-abrasive lapping plate of sapphire wafers with good overall performance [i.e. high material removal rate (MRR), small surface roughness (Ra) of the wafers after lapping and small lapping plate wear ratio (η)].

The influence of process parameters such as lapping time, abrasive size, abrasive concentration, lapping pressure and lapping speed on MRR, Ra and η of lapping-processed sapphire wafers was studied, and the results were combined with experimental data to establish a regression model. The multi-evaluation index optimisation problem was transformed into a single-index optimisation problem via an entropy method and the grey relational analysis (GRA) to comprehensively evaluate the performance of each parameter.

The results revealed that lapping time, abrasive size, abrasive concentration, lapping pressure and lapping speed had different influence degrees on MRR, Ra and η. Among these parameters, lapping time, lapping speed and abrasive size had the most significant effects on MRR, Ra and η, and the established regression equations predicted the response values of MRR, Ra and η to be 99.56%, 99.51% and 93.88% and the relative errors between the predicted and actual measured values were <12%, respectively. With increased lapping time, MRR, Ra and η gradually decreased. With increased abrasive size, MRR increased nearly linearly, whereas Ra and η initially decreased but subsequently increased. With an increase in abrasive concentration, MRR, Ra and η initially increased but subsequently decreased. With increased lapping pressure, MRR and η increased nearly linearly and continuously, whereas Ra decreased nearly linearly and continuously. With increased lapping speed, Ra initially decreased sharply but subsequently increased gradually, whereas η initially increased sharply but subsequently decreased gradually; however, the change in MRR was not significant. Comparing the optimised results obtained via the analysis of influence law, the parameters optimised via the entropy method and GRA were used to obtain sapphire wafers lapping with an MRR of 4.26 µm/min, Ra of 0.141 µm and η of 25.08, and the lapping effect was significantly improved.

Therefore, GRA can provide new ideas for ultra-precision processing and process optimisation of semiconductor materials such as sapphire wafers.

Even though austenitic stainless steels have been extensively used in industries, owing to some of the characteristics of the material, its performance in machining is difficult to understand, in particular at high cutting speeds. There is no availability of dependable and in-depth studies pertinent to this matter. In this work, performance of AISI 304 austenitic stainless steel was studied in terms of surface roughness (Ra) and material removal rate (MRR) at high cutting speeds. Subsequently, parametric optimization and prediction for responses were carried out.

Turning operations were conducted using L9 orthogonal array and the outcomes were analyzed to attain optimal set of machining parameters for the responses using signal-to-noise (S/N) ratio and Pareto analysis of variance (ANOVA). In the present work, the cutting speed values were considered beyond the recommended range as designated by tool manufacturers. Finally, multiple regression models were developed to predict responses.

From the results, 350 m/min was found to be a significant speed. The investigation reveals that even though the speeds are taken beyond the recommended values, the results are favorable. The optimal machining parameters values for surface quality obtained were cutting speed of 350 m/min, feed of 0.15 mm/rev and depth of cut of 2.0 mm. In case of MRR, the optimal values were: cutting speed of 400 m/min, feed of 0.25 mm/rev and depth of cut of 2.0 mm. It was found out that there was an improvement in Ra and MRR (around 15 and 4%) due to optimization. The results indicate that Pareto ANOVA is easier than S/N ratio. This revealed that the feed rate and depth of cut were mostly affected parameters for Ra and MRR. The developed models are capable of predicting the responses accurately.

The outcome of the work reveals that even though the speeds were taken beyond the recommended value, the results are favorable for manufacturing industries when the tool cost is considered insignificant.

No work was reported on machining of the chosen material beyond the recommended cutting speed. Moreover, it was observed from the past works that cutting speeds were limited to 100–300 m/min.

This study aims to understand the current production scenario emphasizing the significance of green manufacturing in achieving economic and environmental sustainability goals to fulfil future needs; to determine the viability of particular strategies and actions performed to increase the process efficiency of electrical discharge machining; and to uphold the values of sustainability in the nonconventional manufacturing sector and to identify future works in this regard.

A thorough analysis of numerous experimental studies and findings is conducted. This prominent nontraditional machining process’s potential machinability and sustainability challenges are discussed, along with the current research to alleviate them. The focus is placed on modifications to the dielectric fluid, choosing affordable substitutes and treating consumable tool electrodes.

Trans-esterified vegetable oils, which are biodegradable and can be used as a substitute for conventional dielectric fluids, provide pollution-free machining with enhanced surface finish and material removal rates. Modifying the dielectric fluid with specific nanomaterials could increase the machining rate and demonstrate a decrease in machining flaws such as micropores, globules and microcracks. Tool electrodes subjected to cryogenic treatment have shown reduced tool metal consumption and downtime for the setup.

The findings suggested eco-friendly machining techniques and optimized control settings that reduce energy consumption, lowering operating expenses and carbon footprints. Using eco-friendly dielectrics, including vegetable oils or biodegradable dielectric fluids, might lessen the adverse effects of the electrical discharge machine operations on the environment. Adopting sustainable practices might enhance a business’s reputation with the public, shareholders and clients because sustainability is becoming increasingly significant across various industries.

A detailed general review of green nontraditional electrical discharge machining process is provided, from high-quality indexed journals. The findings and results contemplated in this review paper can lead the research community to collectively apply it in sustainable techniques to enhance machinability and reduce environmental effects.

The purpose of this paper is to develop a mathematical model for metal removal rate and surface roughness through Taguchi method and analyse the influence of the individual input machining parameters (cutting speed, feed rate, helix angle, depth of cut and wt% on the responses in milling of aluminium-titanium diboride metal matrix composite (MMC) with solid carbide end mill cutter coated with nano-crystals.

Taguchi OA is used to optimise the material removal rate (MRR) and Surface Roughness by developing a mathematical model. End Milling is used to create slots by combining various input parameters. Five factors, three-level Taguchi method is employed to carry out the experimental investigation. Fuzzy logic is used to find the optimal cutting factors for surface roughness (Ra) and MRR. The factors considered were weight percentage of TiB₂, cutting speed, depth of cut and feed rate. The plan for the experiments and analysis was based on the Taguchi L27 orthogonal array with five factors and three levels. MINITAB 17 software is used for regression, S/N ratio and analysis of variance. MATLAB 7.10.0 is used to perform the fuzzy logics systems.

Using fuzzy logics, multi-response performance index is generated, with which the authors can identify the correct combination of input parameters to get higher MRR and lower surface roughness value with the chosen range with 95 per cent confidence intervals. Using such a model, remarkable savings in time and cost can be obtained.

Machinability characteristics in Al-TiB₂ MMC based on the Taguchi method with fuzzy logic has not been analysed previously.

In electrical discharge machining (EDM) process, the production of separate electrodes for rough, semi‐rough and finish machining of dies and moulds having complex surfaces, results in high cost and long lead‐time in manufacturing. The purpose of this paper is to describe the machining performance of electrodes formed by using copper wire bunches (WBs) positioned to conform the surface to be machined was experimentally and theoretically analyzed. In the study, the variations in the machining rate, electrode wear rate, relative wear and workpiece surface roughness were examined for various discharge current and pulse‐time settings.

Copper WBs positioned to conform the surface to be machined in electric discharge machining. The variations in the machining rate, electrode wear rate, relative wear and workpiece surface roughness were examined experimentally for various discharge current and pulse‐time settings. The WB electrodes (WBEs) are proven to be satisfactory as electrodes for roughing operations in electric discharge machining.

The increase in number of wires and pulse energy result in decrease of relative wear for each wire in the electrode. The increase in number of wires in electrodes causes increase in machining area and in machining time in WBE method. With the increase of discharge current and pulse time, the electrode wear rate and material removal values increase and machining time decreases. By using the mathematical models obtained from the result of the experiments, the electrode wear rate, material removal rate, relative wear and the set length of wires for the desired cavity profile can be calculated. The labor cost of electrode manufacturing in the WBE method is lower compared to conventional solid electrodes. The use of WBE method for rough machining decreases machining cost and time. The use of WBE method decreases both the number of the electrodes required and the delay in starting machining due to the preparation of electrode in EDM.

This paper introduces the benefits of using WBE in electric discharge machining; wear and material removal characteristics of WBEs are introduced; the surface roughness characteristics of surfaces produced by WBEs are examined experimentally; and the effect of number of wires used in WBEs given (experimental findings).

This study aims to investigate the optimal process parameters of the wire-cut electrical discharge machining (WCEDM) for the machining of the GZR-AA7475 hybrid metal matrix composite (HMMC). HMMCs are prepared with 2 Wt.% graphite and 4 Wt.% zirconium dioxide reinforced with aluminium alloy 7475 (GZR-AA7475) composite by using the stir casting method. The objective is to enhance the mechanical properties of the material while preserving its unique features. WCEDM with a 0.18 mm molybdenum wire electrode is used for machining the composite.

To conduct experimental studies, a Taguchi L27 orthogonal array was adopted. Input variables such as peak current (I_p), pulse-on-time (T_ON) and flushing pressure (P_F) were used. The effect of process parameters on the output responses, such as material removal rate (MRR), surface roughness rate (SRR) and wire wear ratio (WWR), were investigated. The grey relational analysis (GRA) is used to obtain the optimal combination of the process parameters. Analysis of variance (ANOVA) was also used to identify the significant process parameters affecting the output responses.

Results from the current study concluded that the optimal condition for grey relational grade is obtained at T_ON = 105 µs, I_p = 100 A and P_F = 90 kg/cm². Peak current is the most prominent parameter influencing the MRR, whereas SRR and WRR are highly influenced by flushing pressure.

Identifying the optimal process parameters in WCEDM for machining of GZR-AA7475 HMMC. ANOVA and GRA are used to obtain the optimal combination of the process parameters.