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A colossal research work is being consummated to propose the optimal machining parameters while necessitating current machining techniques to attain elegant products. This research work foregrounded the optimum process parameters of die sinking EDM with 8mm diameter copper electrode during machining AISI D2 steel. Taguchi’s L9 OA method was adopted...
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In the current study, an optimization process of powder-mixed electrical discharge machining (PMEDM) process when machining cylindrically shaped parts made of hardened 90CrSi steel is reported. In this study, SiC powder was mixed into the Diel MS 7000 dielectric solution. Additionally, graphite was chosen as the electrode material. The multi-object...
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Citations
... Powdermixed EDM and Nanopowder-mixed EDM have been developed as advanced methods for improving machining performance in difficult-to-cut materials, such as Al-Z-Mg composites reinforced with Si3N4, particularly when using nickel-coated and uncoated brass electrodes. The process of micro-hole machining, taking into account variables like pulse on time, voltage, input current, and capacitance, has demonstrated significant effects on MRR and EWR, with SEM analysis providing valuable insights into surface morphology alterations (Jana et al. 2021). Taguchi's L9 orthogonal array and multi-criteria decision-making techniques, such as TOPSIS and grey relational analysis, were used in this study to improve die-sinking EDM settings for AISI D2 steel machining using a copper electrode. ...
This paper presents an experimental study on the electrical discharge machining (EDM) of AISI D2 die steel using an Al-Ni composite electrode. The investigation focuses on the influence of input parameters like current, pulse duration, and pulse interval, on key output parameters such as material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR). EDM oil was employed as the dielectric fluid. Grey relational analysis (GRA) was utilized for designing and conducting the experiments using the Taguchi L9 method. The ANN model showed excellent predictive accuracy with a perfect correlation coefficient (R) of 1.00, indicating strong capability in forecasting MRR based on machining parameters. GRA further confirmed that higher current settings and longer pulse-off times effectively reduce tool wear, suggesting that the ANN model accurately reflects the conditions that minimize TWR. The ANN model achieved strong predictive accuracy for SR, with high correlation coefficients, although with slightly higher mean squared error (MSE) in testing.
... Another relevant work by Das et al. introduced transesterified neem as a green dielectric and unveiled that it can ensure better surface textures due to the repeated overlapping of the radially extended craters and reduce machining time (Das et al., 2020a). Some of the other significant experimental investigations conducted using various vegetable oils include the works extracting the (Supawi et al., 2021), (Ahmad et al., 2020), canola oil (Jana et al., 2021;Rao et al., 2020) and neem oil (Das et al., 2019). Nonetheless, the study revealed the superiority of the jatropha oil-based dielectric fluid over the others, and it is being further investigated. ...
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
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.
Electrical Discharge Machining Process, also termed as Spark Erosion Machining has been effectively in practice in different industrial sectors for machining variety of hard-to-cut materials. However, this machining method is associated with number of limitations including toxic gases emissions, fire hazards, waste dielectric disposal problems, etc. With a purpose of reducing such disadvantages, new class of dielectric fluids derived from vegetable oils have been put in practice over past number of years. Common examples of vegetable based dielectrics in EDM process are Jatropha oil, sunflower oil, canola oil, neem oil, pongamia pinnata oil, etc. Use of such green dielectrics has added to the sustainability aspect while machining through EDM process. This review article highlights the effect of machining different hard materials in bio-based dielectric fluids to machining in conventional hydrocarbon oils by comparing their material removal rates, electrode wear rates, surface finish, and surface topographies. Moreover, areas in this field of green EDM which further need to be studied are also highlighted and can be taken as prospects for future study.
The present study examines the cutting of X210Cr12 cold work tool steel by a triple (CVD) coated carbide tool (Al2O3/TiC/TiCN). This is an experimental investigation followed by modeling and optimization inherent to the cutting process of the above material. The first part of this work deals with carrying out experimental tests to evaluate the effects of cutting parameters on the flank wear (Vb) evolution and workpiece surface topography including 2D and 3D functional parameters. In the second part, a Taguchi L16 (4^3 2^1) design of experiment was adopted to optimize cutting conditions. For that, a single objective optimization based on Taguchi analysis using the signal/noise (S/N) ratio was performed. In addition, multi-criteria optimization was conducted by (GRA, MOORA, DEAR, WASPAS) methods using the (S/N) report. The desired objective corresponds to the minimization of Ra, Fz, and Pc and the maximization of MRR. A comparison between the optimal regimes found by the different methods used has been analyzed and discussed. Finally, confirmation tests were conducted to determine the results of the optimal regimes obtained outside the experimental design.
Multiobjective optimization (MOO) helps to achieve simultaneous improvement of more than one output characteristic in machining processes where complex interaction between the input parameter exists. This study focuses on the comparative analysis of design of experiment (DoE)-based grey relational analysis (GRA) combined with principal component analysis (PCA) and analytic hierarchy process (AHP). Experiments were conducted with millisecond (ms) duration pulsed Nd: YAG laser using the Box–Behnken design (BBD) approach of the response surface methodology (RSM) at three different levels of input parameters. The output parameters, i.e., hole circularity at top (HCT), hole circularity at bottom (HCB), and hole taper (HT), were determined for various input parameters like pulse current (I), pulse width ([Formula: see text]), gas pressure ([Formula: see text]), workpiece thickness ([Formula: see text]), and incidence angle ([Formula: see text]) during laser percussion inclined hole drilling (LPIHD) in the carbon fiber reinforced polymer (CFRP) of three different thickness, i.e., 1[Formula: see text]mm, 3[Formula: see text]mm, and 5[Formula: see text]mm at incidence angles of 0, 10, and 20 degrees. Multiobjective function based on RSM has been developed for GRA-PCA and GRA-AHP and further optimizations were performed using the desirability approach of RSM. The analysis revealed that the angle of incidence is the most significant factor for controlling the output parameters. Interaction of pulse current and thickness ([Formula: see text]) has a major impact on output responses. The GRA-PCA approach gives the average improvement of 2%, 9%, and 37%, respectively, for HCT, HCB, and HT, whereas in the case of GRA-AHP, the corresponding improvements are only 1%, 6%, and 11%. Therefore, the GRA-PCA approach is a more effective tool for the MOO of LPIHD in CFRP.
