Values Of Material Removal Rate Research Articles

Development of optimum performance model during spark-eroded processing of rheocasted Al6061/Cenosphere MMCs

ABSTRACT In the present study, an improved wettability casting route was used to prepare lightweight structural materials. Using the compo casting process, an Al6061 alloy was created with cenosphere particles at various weight percentages (2, 4, 6, and 8 wt%). The molten aluminium slurry incorporated hollow alumina silicate particulates. X-ray diffraction (XRD) analysis of the aluminium matrix composites (AMCs) confirmed the presence of cenospheres without any intermetallic components. Further processing of the metal matrix composites (MMCs) was conducted using electric discharge machining (EDM) with a circular copper electrode. The EDM process parameters were controlled to measure response variables such as material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR). The effects of different combinations of machining parameters – including pulse current, pulse-on time, reinforcement percentage, and flushing pressure – on these performance characteristics were observed. Experimental trials were designed using the face-centred central composite design (CCD) of the response surface methodology (RSM). Optimal process variable conditions led to significant improvements in surface finish. Additionally, an artificial neural network (ANN) model was used to determine the best conditions for EDM processing. The ANN model demonstrated a strong correlation coefficient of 0.99 between the predicted and experimental values of MRR, TWR, and SR.

Simulation and experimental study for enhancing surface integrity of micro-slots processed on Nimonic-263 super alloy via electrochemical machining

ABSTRACT The potential of micro electrochemical slotting is significant due to its adaptability and usefulness across diverse manufacturing applications. This technique holds potential, particularly for handling advanced engineering materials like superalloys, with a focus on applications requiring high strength, i.e., micro-cutting for gas-turbine parts, biomedical applications, etc. With this view, this article has been attempted to explore the influence of various considered machining factors, namely as; applied potential difference, tool feed rate (TFR), pulse supply, and modes of tool insulation on the performance measures, i.e. material removal rate (MRR) and surface roughness (Ra) while attempting micro-slotting in Nimonic-263 superalloy work samples. The entire experimentation was conducted on the in-house fabricated 3-axis micro-electrochemical setup designed for performing various complex machining operations at a miniature scale. Furthermore, this study has also been focused toward investigating the impact of varying the electrical conductivity by employing different tool materials (i.e. copper and SS304) on the process characteristics measured. The observed effects of the tool electrode’s conductivity have also been expressed and supported by performing the simulation for electric field distribution using COMSOL Multiphysics software. The experimental results have revealed that the process input variables remarkably influence MRR and Ra, mainly applied voltage and TFR. The best values of MRR and Ra attained with SS304 and copper tool electrodes were 1.521 mg/min and 0.721 mg/min, and 0.038 µm and 0.029 µm, correspondingly. The microstructure analysis has further been conducted on machined micro-slotted work samples that provided detailed insights into various surface integrity aspects, which are essential for microdevice applications.

Machinability and pulse characteristics of Ti-16Al-14Nb (α/β) alloy in wire-electric discharge machining process: A surface integrity study

The goal of the present work is to produce the efficient cutting of Ti-16Al-14Nb (α/β) alloy through wire-electric discharge machining and contemplate the terminologies such as machining ability, surface integrity and material removing capability. For this, the experimentation has been designed by considering three process parameters, pulse-on time ( Ton), pulse-off time ( Toff) and peak current ( Ip) at three significant levels (low, high, intermediate) in L27 order designed from design of experiments. The effect of these process variables on pulse characteristics, surface roughness ( Ra), kerfwidth ( Kw) and material removal rate ( MRR) is analyzed and mathematically modeled with analysis of variance. The results state that the highest MRR (0.521, 0.51, 0.506 mm3/sec) and low surface roughness (8.91, 8.89, 8.68 µm) values are observed at the highest level (110 µs, 15 µs, 8 A). If the pulse duration is kept at low ( Ton = 40µs, Toff = 3µs), the increase in peak current from 3 A to 8 A leads to a 64.54% increase in MRR and a 52.9% increase in Ra values. ANOVA results stated that Ton has contributed 20.4%, 35.8% and 19.3%, and Ip has contributed 43.1%, 30.5% and 46.6% influence on MRR, Kw and Ra respectively. The voltage–current characteristics studies confirmed that the strong intense pulses at a higher peak current (8 A) resulted in the increased MRR (0.521 mm3/sec) and Ra (8.43 µm) leading to the formation of swages and ridges. The surface integrity analysis derived from Abbott–Firestone curve agreed that the lowest level has shown better skewness ( Rsk = −0.274) and at highest level showed a larger deviation in skewness ( Rsk = +2.672) signifies that higher asymmetry (poor) of the surface.

PERFORMANCE ENHANCEMENT OF BRASS EDM ELECTRODES WITH CRYOGENIC TREATMENT WHILE MACHINING THE COLD WORK STEEL AISI D2

This study investigates the performance of deep cryogenically treated brass (CuZn25Al5) electrodes in the die-sink EDM process. Two different cryogenic treatment durations, 6 h and 12 h, were applied to 8 mm diameter electrodes, and their effects were compared to untreated electrodes. The machining tests were conducted under moderate and aggressive conditions. In the machining tests, the 6-h cryo-treated electrode exhibited a 16.8% increase in material removal rate (MRR) under moderate conditions and a 19.7% increase under aggressive conditions compared to the reference electrode. The 12-h cryo-treated electrode showed similar MRR values to the reference electrode but improved tool wear resistance by 9.4% under moderate conditions. The kerf angle was minimized, indicating better hole verticality, in the 6-h cryo-treated electrode group. The improvement in machining performance was attributed to the enhancement in electrical conductivity of the electrodes, which increased by 28% for the 6-h cryo-treated electrode and 20% for the 12-h cryo-treated electrode. X-ray diffraction (XRD) analysis revealed shifts in peak positions and possible phase transformations due to cryogenic treatment. Surface roughness measurements showed improved surface conditions in the cryo-treated electrodes under aggressive conditions. The results indicate that cryogenic treatment enhances MRR, reduces tool wear, and improves surface quality in die-sink EDM. These improvements are attributed to increased electrical conductivity and changes in the internal structure of the brass electrode.

Prediction of machining performances in powder mixed electro-discharge machining to process skd61 steel by response surface methodology

In electro-discharge machining (EDM) with mixing powder, it is called powder mixed electro-discharge machining (PMEDM), then machining performances- i.e. material removal rate(MRR) and tool wear rate (TWR) has great significance in evaluating the effectiveness and machining accuracy of the machining method. Therefore, in this study, response surface methodology (RSM) was utilized for estimating functions of process variables {comprising peak current (Ip), pulse on time (Ton), and powder concentration (Cp)} for the machining performances for processing SKD61 steel during EDM process with tungsten compound powder. Box-Behnken matrix was utilized for designing and conducting a series of empirical trials. Analysis of variance (ANOVA) was applied to evaluate the adequate of predictive models. The outcomes reveal that the predicted models of MRR and TWR have a high precision with R2 values of MRR and TWR being 99.2% and 99.11%, respectively. The error comparison of the predictive and empirical values for the confirmed experiments is less than 5%, this once again consolidates that the developed models' accuracy. These development models can efficiently prognosticate the desired machining performances of the PMEDM method for processing SKD61 steel

Evaluating the optimum abrasive water jet machinability for CARALL composites with various fiber orientations

AbstractCarbon Fiber Reinforced Aluminum Laminated (CARALL) composites are widely used in aircraft structures due to their ability to be produced in different shapes with desired properties and their high impact resistance properties. As with other layered composite materials, processing of CARALL composites by conventional manufacturing methods results in many damage mechanisms such as fiber breakage, deformation in the hole region, stress concentration, resin‐fiber separation and microcracks. One of the modern manufacturing methods, Abrasive Water Jet (AWJ), is a processing method in which the material is removed by abrasion and almost any material can be cut without thermal degradation. There are no experimental studies in the literature on the drilling of CARALL composites by modern manufacturing methods. The aim of this study is to investigate the impact of machining parameters on the output variables (kerf taper angle (K), roundness error (Re) and material removal rate (MRR)) as well as the effect of fiber orientation on the drilling of CARALL composites with different fiber orientations on an AWJ machine. PROMETHEE‐GAIA weighted by Entropy Weighting Method were used to ascertain the optimum levels of control factors. CARALL composites with different fiber orientations were drilled with an 8 mm diameter AWJ with three different water pressures, three different nozzle feed rates. With PROMETHEE‐GAIA multi‐criteria optimization method, the optimum levels of the factors that provide both minimum Re and K values and maximum MRR value were obtained with twill woven material, 1680 mm/min feed rate and 1680 bar water pressure.Highlights CARALL composite materials with two different fiber orientations (twill weave and UD) were used. CARALL composite materials were drilled at different machining parameters. Abrasive water jet was used in drilling experiments. Optimum drilling parameters were determined to achieve minimum roundness error, minimum kerf angle and maximum material removal rate. PROMETHEE‐GAIA was used as a multi‐criteria decision‐making method.

Modelling the material removal obtained using a pneumatically configurable polishing tool subjected to a reciprocating linear feed

A nanofinishing technique - Pneumatically Configurable Polishing (PCP) process can be used for producing surface roughness of the order of a few nanometers on surfaces. It is a deterministic polishing process which employs pneumatic pressure for precise control of finishing forces across the polishing spot. The material removal rate is an important characteristic for determining the final surface generated after polishing. The material removal mechanism of PCP process typically exhibits multidisciplinary complexity due to simultaneous contribution of various process parameters. A mathematical model has been proposed in this study to achieve an in-depth understanding of the process physics. The model is developed using the fundamental tenets of contact behaviour between the tool and workpiece, and study of the microscopic material removal caused by a single abrasive particle. The polishing tool undergoes a reciprocating linear feed to polish a linear strip of the work surface. Various process parameters such as feed rate, tool rotational speed, working gap, mean diameter of abrasive particles, slurry concentration etc have been incorporated in the model as per the physics of the process. In order to validate the model, finishing experiments and MATLAB simulations have been conducted under similar polishing conditions to estimate the prediction error. The material depth removal rate in the PC polishing of die steel was found to range between 39 nm/min and 257 nm/min. The error between the experimental and predicted values of material removal rate was found within a range of 2.7 %–15.9 %. The repeatability of final surface roughness values and MRR obtained is ±0.007 μm and ±10 nm/min respectively. The developed model helps to make the PCP process more predictable and provides valuable insights into the various parameters which predominantly affect the material removal. The simulation of the gradual evolution of the surface profile has been obtained using the developed model.

Prediction and Multiparametric Optimization of the Machined Surface Quality of Tool Steels in Precise Wire Electrical Discharge Machining

This article describes a proposed procedure for multiparametric optimization of the quality of machined surfaces, including mathematical models that can predict the high quality of a precisely machined surface and, at the same time, the high productivity of the process in WEDM of tool steels. The experimental research was carried out using the full DoE factorial design method, which has four technological parameters. The measured output qualitative parameter Surface Roughness (SR) and the output quantitative parameter Material Removal Rate (MRR) were evaluated using the Grey Relational Analysis (GRA) and Analysis of Variance (ANOVA) methods. Multiple Regression Models (MRM) were developed to represent the multiple responses of the investigated tool steels using a regression tool set. The results of the multiparametric optimization revealed a correlation between the input variable parameters of the electrical discharge process, while the favorable results of the observed output-dependent parameters SR and MRR were coupled to the parameters of low peak current I, low value of pulse on-time duration ton, low voltage of discharge U, and high value of pulse off-time duration toff. Based on the multiparametric optimization, key results were obtained that demonstrated the mutual dependence of the observed output process parameters. An optimum SR value of 1.50 μm was obtained with L8-level settings for the input variable parameters I, ton, U, and toff (2 A, 32 μs, 90 V, and 20 μs, respectively) and an MRR value of 12.50 mm3·min−1 was achieved.

Effect of pulse time (Ton), pause time (Toff), peak current (Ip) on MRR and surface roughness of Cu–Al–Mn ternary shape memory alloy using wire EDM

Shape memory and super elasticity are two outstanding properties of Cu–Al–Mn SMAs together with additional copper-based shape memory alloys that make them superior to NiTi alloys. It's quite hard to machine Cu–Al–Mn SMA. The machinability properties of Cu–Al–Mn SMAs during Wire Electrical Discharge Machining (WEDM) were experimentally investigated using molybdenum wire as the electrode material. Material Removal Rate (MRR) and Surface Roughness (SR) are two machining qualities that are studied in relation to the combinational values of pulse time (Ton), pause time (Toff), and peak current (Ip), which are selected as the changeable input process factors. From the experimental investigation, it was found that both MRR and Ra values were increased with an increase in pulse on time(Ton), pulse off time(Toff), and peak current (IP)values. Because the wire electrode contains maximum current under these conditions, it is easy to remove more material at the tool and work material interface, resulting in moderate surface finish. Surface quality was higher on samples machined at low energy input than it was on samples machined at high energy input. This SEM micrograph clearly shows that a lower pulse on time produces a superior surface quality.SEM images and the analysis of the machined surface morphology on the surface of the CAM7 alloy clearly showed that the machined surface of the alloy had a lower surface roughness value at a lower Ip-2A and was associated with a higher surface roughness value at a higher Ip-6A, as well as a lot of uncleared debris and blow holes.

Bi-objective optimization of an EDM process with Cu-MWCNT composite tool using single-valued neutrosophic grey relational analysis

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.

Parametric study of WEDM of titanium grade 12 using RSM and desirability approach

The present experimental study aims to scrutinize the effect of different process parameters on the material removal rate (MRR) and surface roughness (SR) of titanium grade 12 alloy during wire electro-discharge machining (WEDM) using response surface methodology. Four parameters (pulse-on time, pulse-off time, wire feed and gap voltage) and three levels of each selected variable are considered to conduct the experimental work. Depending on experimental results, a mathematical model is generated for both MRR and SR. An analysis of variance (Anova) study is performed to find significant process parameters. The Anova results show that the developed models for both MRR and SR are significant, and pulse-on time is found to be the most significant parameter. Additionally, the desirability approach is used to scrutinize the single-objective and multi-objective criteria of response variables. The desirability functions for all of the cases are found to be 1. The maximum MRR is observed to be 12.4845 mm3/s, while the minimum value of SR is found to be 1.4911 μm. For multi-objective optimization, the maximum value of MRR and the minimum value of SR are obtained as 12.0942 mm3/min and 1.7167 μm, respectively. Finally, the surface morphology of the machined surfaces is examined using scanning electron microscopy micrographs.

Using VIKOR and RSM-DA in the optimization of dry turning of 9XC steel

Dry turning is an effective method for reducing the production costs and environmental impact of machining processes. In this study, the effect of cutting speed (Vc), feed rate (fz), and depth of cut (ap) on the surface roughness (Ra) and material removal rate (MRR) of 9XC steel during dry turning was investigated. A Box-Behnken experimental design was employed to analyze the main effects and interaction effects of these cutting parameters. In this research, the combining Response Surface Methodology - Desirability Approach (RSM-DA) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method were both employed for solving multiple objective optimization problems, and their performance was compared. The results from both methods can be assessed based on their ability to identify the optimal set of parameters that simultaneously optimize surface quality and production rate, as well as their computational efficiency and ease of implementation. Both RSM-DA and VIKOR have been found effective for solving multi-objective optimization problems, such as optimizing cutting parameters in dry turning. While RSM-DA is a statistical tool that combines multiple objectives into a single function, VIKOR is a decision-making method that ranks alternatives based on multiple criteria. The choice of which method to use depends on the specific requirements of the problem and the availability of resources for implementation. The research results show that both VIKOR and RSM-DA are suitable for solving the multi-objective optimization problem of the turning process. According to the VIKOR method, the optimum cutting conditions were found to be a cutting speed Vc of 120 m/min, a depth of cut ap of 0.1 mm a feed rate fz of 0.06 mm/rev, and, which resulted in a surface roughness of 0.209 um and a material removal rate of 0.72 cm3/min. Meanwhile, RSM-DA predicts the optimal Ra and MRR values of 0.254 um and 3.36 cm3/min, respectively; corresponding to the Vc of 180m/min, fz of 0.06mm/rev and ap of 0.3mm; That means, the increasing the value of surface roughness by 21.5% will increase the MRR by 366.7%. The findings of this study can provide guidance for selecting the appropriate cutting parameters for dry turning of 9XC steel to achieve desired surface roughness Ra and material removal rate MRR in the specific case.

Optimisation of free-abrasive assisted lapping process with vitrified bonded diamond plates for sapphire substrates

To improve the processing performance of vitrified bonded diamond fixed-abrasive lapping plates for processing sapphire substrates, a free-abrasive was added to the lapping slurry to enhance the self-dressing ability of the lapping plate to achieve efficient and high-quality processing of sapphire substrates. The processing effectiveness and mechanism of a free-abrasive assisted fixed-abrasive lapping plates (FAAFALP) lapping process for sapphire substrates were analysed and revealed via a single-factor experiment. To optimise the lapping process of the FAAFALP of sapphire substrates with good overall performance (high material removal rate (MRR), minor surface roughness (Ra) and big lapping plate wear ratio (η)), the effects and the optimal parameters combination of the lapping pressure, lapping speed and free-abrasive concentration on MRR, Ra and η of lapping-processed sapphire substrates were investigated using orthogonal experiments. Furthermore, the experimental results were combined with process parameters to establish a regression model. The multi-evaluation index optimisation problem was transformed into a single-index optimisation problem via the grey relational analysis (GRA) to evaluate each parameter's performance comprehensively. The results revealed that an MRR increased by 22.2 % to 2.48 μm/min, the smallest surface roughness Ra of 0.141 μm, and the lapping plate wear ratio η relatively increased to 14.88 was obtained when a free-abrasive of SiO2 with a particle size of 14 μm was added into lapping slurry. Compared with no free-abrasive lapping process, free-abrasive can significantly improve the lapping plate's self-dressing ability and enhance the sapphire substrates' processing effect. The lapping speed, lapping pressure and free-abrasive concentration had different influence degrees on MRR, Ra and η. The established regression equations predicted the response values of MRR, Ra and η to be 99.87 %, 99.06 % and 98.59 %, respectively, and the relative errors between the predicted and actual measured values were <12 %. With increased lapping speed, MRR initially decreased but subsequently increased, and Ra and η gradually decreased. MRR and η continuously increased with increased lapping pressure, whereas Ra decreased. With increased free-abrasive concentration, MRR, Ra and η initially increased but subsequently decreased. Comparing the optimised results obtained by intuitive analysis, the parameters optimised via the GRA were used to obtain sapphire substrates lapping with an MRR of 3.81 μm/min, Ra of 0.133 μm and η of 20.4, and the overall lapping performance was better 42.92 %, 102.90 % and 43.60 % than that of intuitive analysis for MRR, Ra and η. Therefore, combining orthogonal experiments and GRA can provide new ideas for optimising the FAAFALP lapping process for sapphire substrates.

Multi-objective parametric optimization of electrochemical machining of Inconel-625 superalloy

The high hardness value of Inconel-625 super alloy makes it difficult to machine with traditional machining methods. In this study, the machining of Inconel-625 has been attempted with electrochemical machining. The influence of input process parameters—voltage, feed rate, and flow rate of electrolyte has been studied on the output responses—material removal rate (MRR) and average surface roughness (SR). The experiments were performed following the central composite rotatable design of the response surface methodology. Analysis of variance has been used to test the significance of the process parameters and the model. A comprehensive empirical model representing the relationship between the process parameters and the response parameters has been developed. Further, the desirability function approach was used to acquire the optimal set of parameters. The optimal values of MRR and SR obtained in the study are 0.192837 gm./min and 0.99 μm, respectively, corresponding to the optimum settings of voltage, feed rate of the tool, and flow rate of electrolyte at 13.7 V, 0.20 mm/min, and 2.8 lit/min, respectively. The optimum settings so attained have been substantiated using confirmation experiments. The Confirmation tests show that the error between predicted and experimental values of MRR and SR was 2.02% and 4.8%, respectively, which fall in the acceptable range. Moreover, the surface characteristics of the machined area have been investigated using field emission scanning electron microscopy and 3D optical profilometer to analyze the machined surface's microstructure and 3D surface characteristics.

Electric discharge machining of hybrid composite with bio-dielectrics for sustainable developments

ABSTRACT The hybrid composite (Al-SiC-Ni) has a wide range of applications due to its high strength-to-weight ratio and exceptional mechanical and wears resistance properties. Electric Discharge Machining (EDM) is a common method for machining high-strength composites. However, one significant challenge associated with EDM is the emission of harmful fumes caused by the thermal cracking of hydrocarbon-based dielectrics, as well as the rate of material removal, both of which impact process productivity. However, no research has been conducted on the effect of non-edible biodiesel-based bio-dielectrics on the EDM of hybrid composites (Al-SiC-Ni). As a result, the primary goal of this research is to assess the environmental effects of machining. This study specifically investigates the impact of four types of non-edible biodiesel-based bio-dielectrics on key EDM process output parameters such as material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR). The EDM performance of the hybrid composite (Al-SiC-Ni) was compared to that of three electrode materials (copper, brass, and graphite) and four bio-diesel-based bio-dielectrics such as Neem biodiesel (NBD), Jatropha biodiesel (JBD), Pongamia biodiesel (PBD), and Polanga biodiesel (POBD). From investigation, it has been observed that the maximum value of material removal rate (MRR) for POBD using a graphite electrode was 18.54 mg/min, which was 58.5% higher than the MRR for JBD using a brass electrode (7.17 mg/min). And it was found that the MRR with POBD was 108.15% higher than with kerosene oil. The graphite as mentioned above electrode obtains its smoothest surface under POBD. This roughness value is 77.41% lower than the JBD value obtained. Tool wear is observed lowest in the brass electrode in conjunction with the JBD. It is 68.88% lower than the TWR value obtained with PBD using the same electrode material. The results indicated that biodiesel derived from non-edible oils could be a promising dielectric for the future of the EDM process.

Artificial intelligence for experimental investigation and optimal process parameter selection in PM-EDM of nimonic alloy 901

Electrical discharge machining (EDM), a widely used non-contact machining method, employs electric discharge to remove conductive material from workpieces. This study focused on experimentally investigating and optimizing input process parameters for the PM-EDM process of a Nimonic alloy 901 (NA-901) workpiece with a silver electrode. The silicon carbide (SiC) powder particles were explored for their exceptional properties, including high temperature resistance, hardness, thermal conductivity, and resistance to corrosion and oxidation. The study evaluated the impact of input process parameters such as servo voltage (Vs), powder concentration (Cp), pulse-on-time (Ton), and peak current (Ip) on surface roughness rate (SRR),tool wear rate (TWR), and material removal rate (MRR). The Taguchi design approach with an L18 orthogonal array was used to identify the optimal parameter combination based on signal-to-noise (S/N) ratio analysis. To improve optimization, a feed-forward backpropagation neural network (FF-BPNN)was utilized to approximate solutions. The results of the experimental MRR confirmation test (E-MRR) were compared to the MRR values predicted using the FF-BPNN model (P-MRR). Similarly, the SRR (E-SRR) and the TWR (E-TWR) were compared to the predicted SRR and TWR obtained from the proposed FF-BPNN model. In summary, this study presents an experimental examination and optimization of input process parameters in the PM-EDM process of an NA-901 workpiece with a silver electrode.The use of SiC powder particles, the impact of input process parameters, and optimization were explored using Taguchi design and FF-BPNN techniques. This study's results demonstrate these approaches' effectiveness in achieving optimal PM-EDM process parameters.Finally, results revealed E-MRR as 6.894, P-MRR as 6.8913, E-SRR as 0.891, P-SRR as 0.897, E-TWR as 0.116, and P-TWR as 0.015.

Experimental Investigation and Modelling Studies on MHD Convection in Magnetic-assisted -ECDM

ABSTRACT The present work concerns microchannel fabrication using magnetic-assisted electrochemical discharge machining on silica glass. The magnetic field regulates the process by controlling bubble formation and separation adjacent to the tool edge. Due to the applied magnetic and electric flux on the electrolyte and electrode interface, the Lorentz force impacts the bubble establishment and film quality. The fractional bubble coverage decreases with the magnetic field, which increases the current density and affects the discharge frequency. The analytical model is explored here to investigate the magnetic field influences on departure radius. A novel approach has been adopted to couple the Laplace and Navier stokes equations for studying the magnetohydrodynamic effect. The experimental and analytical results reveal that magnetic flux decreases the bubble departure radius. The regression model explains the impact of controllable factors on surface roughness, material removal rate, and width overcut. The multi-response optimization with the hybridization of response surface methodology and grey relation analysis technique provides the optimum value of material removal rate, width overcut and surface roughness as 1.2 mg/min, 0.046 mm, and 1.58 µm, respectively.

Effect of Wiper Edge Geometry on Machining Performance While Turning AISI 1045 Steel in Dry Conditions Using the VIKOR-ML Approach

AISI 1045 can be machined well in all machining operations, namely drilling, milling, turning, broaching and grinding. It has many applications, such as crankshafts, rollers, spindles, shafts, and gears. Wiper geometry has a great influence on cutting forces (Fr, Ff, Fc and R), temperature, material removal rate (MRR) and surface roughness (Ra). Wiper inserts are used to achieve good surface quality and avoid the need to buy a grinding machine. In this paper, an optimization-based investigation into previously reported results for Taguchi’s based L27 orthogonal array experimentations was conducted to further examine effect of the edge geometry on the turning performance of AISI 1045 steel in dry conditions. Three input parameters used in current research include the cutting speed (Vc), feed (f) and depth of cut (ap), while performance measures in this research were Ra, Fr, Ff, Fc, R, temperature (temp) and MRR. The Vise Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method was used to normalize and convert all the performance measures to a single response known as the VIKOR-based performance index (Vi). The machine learning (ML) approach was used for the prediction and optimization of the input variables. A correlation plot is developed between the input variable and Vi using the ML approach. The optimized setting suggested by Vi-ML is Vc: 160 m/min; ap: 1 mm and f: 0.135 mm/rev, and the corresponding value of Vi was 0.2883, while the predicted values of Ra, Fr, Ff, Fc, R, temp and MRR were 2.111 µm, 43.85 N, 159.33 N, 288.13 N, 332,16 N, 554.4 °C and 21,600 mm3/min, respectively.

Electrochemical micromachining and parameter optimization on AZ31 alloy—ANN and TOPSIS techniques

ABSTRACT. Electrochemical micromachining (ECM) is a nontraditional method used for machining operations in hard and light materials with fixed or varying parameters. In this study, magnesium AZ31 alloy was micro machined using two types of electrolyte supply systems, namely electrolyte flooding and minimum quantity electrolyte (MQE). Experimental investigations were performed using TOPSIS and artificial neural network (ANN) techniques with types of electrolyte supply system, electrolyte concentration (EC), duty cycle (%), and machining voltage (V) as the input parameters, and material removal rate (MRR) and over cut (OC) as the outputs. Single and multi-objective parameter optimization was performed using Taguchi, TOPSIS, and ANN techniques. The machined microholes were analyzed using scanning electron microscopy. According to the TOPSIS results, under optimal conditions, a high MRR value and minimum OC of 1.282 μm/s and 66 μm, respectively, were obtained. The results of TOPSIS were verified using the developed ANN architecture.&#x0D; &#x0D; KEY WORDS: Magnesium, AZ31 alloy, Electrochemical micromachining, Optimization, TOPSIS, ANN&#x0D; Bull. Chem. Soc. Ethiop. 2023, 37(5), 1263-1273. &#x0D; DOI: https://dx.doi.org/10.4314/bcse.v37i5.17

Effect of Current and Pulse-on Time on Material Removal Rate and Surface Roughness of Tungsten Carbide in Electric Discharge Machine Die-sinking

The focus of manufacturing for tungsten carbide applications often demands a smooth surface quality as the result of the Electric Discharge Machine (EDM) die-sinking process, especially in the manufacture of die and mold with tungsten carbide material processed using a die-sinking EDM machine. The purpose of this study is to analyze the effect of electric current and pulse-on time on the Material Removal Rate (MRR) and surface roughness of tungsten carbide. Through the experimental method, the parameters varied, namely electric current 17 A, 20 A, 23 A, and pulse-on time 30 µs, 55 µs, and 80 µs. MRR was calculated through weight loss. Surface roughness was obtained from a surface roughness tester and a Scanning Electron Microscope for surface morphology. The results showed that the highest material removal rate was 1.509 mm3/min at 23 A and 30 µs, and the lowest material removal rate was 0.262 mm3/min at 17 A and 80 µs. The highest surface roughness value was 4.278 µm at 23 A and 80 µs. The lowest surface roughness value was 2.166 µm at 17 A and 30 µs. The tungsten carbide surface topography results are crater, globule, crack, and porous. The greater the current used, the higher the MRR value and surface roughness. Meanwhile, the greater the pulse-on time used, the MRR value decreases, and the surface roughness increases.