Pulse-on Time Research Articles

Optimisation of EDM Parameters for Cryogenically Treated EN31 Steel with Copper Tool

EDM has been replacing drilling, milling, grinding, and other traditional machining operations and is now a well-established machining option in many manufacturing industries throughout the world and is capable of machining geometrically complex or hard material components, that are precise and difficult-to-machine such as heat-treated tool steels, composites, superalloys, ceramics, carbides, heat resistant steels, etc. During machining done over EDM machine, with the workpiece, even the tool wears out. This tool wear is not desired as it changes the tool geometry. To overcome this hurdle, cryogenic treatment is carried out for workpiece material before machining. This report presents the optimization of EDM process parameters such as pulse on-time (Ton), pulse off-time (Toff), and Current (I) to obtain the greatest material removal rate (MRR) and less surface roughness (Ra) of EN31 steel with copper as the working electrode for machining.

Multi-objective optimization of process variables for MWCNT-added electro-discharge machining of 316L steel

Fabrication of 316L steel with the desired surface integrity and thin modified recast layer for manufacturing various devices is very challenging using the traditional techniques and requires post-processing. Nevertheless, electro-discharge machining (EDM) is an evolving candidate among the non-traditional processes offering concurrent machining and surface alteration for the instrument manufacturing industry. To explore its full potential, this research work provides a thorough investigation of process variables on the machining performances and surface features primarily required for processing 316L steel in the industry. In this study, nano multi-walled carbon nanotubes (MWCNT) are utilized to improve the machining and surface responses. In addition to this, the parametric optimization is conducted through a Taguchi-based design which assists to obtain the highest material removal rate (MRR) of 42.25 mg/min corresponding to a 10-A peak current, 16-μs pulse-on time, 1-g/l MWCNT amount, and 45% duty cycle while the lowest surface roughness (SR) and recast layer thickness (RLT) of 1.58 μm and 5.243 μm respectively are attained at a 5-A peak current, 8-μs pulse-on time, 0.7-g/l MWCNT amount, and 45% duty cycle. Analysis of variance (ANOVA) reports peak current being the most momentous parameter complied by the MWCNT amount, pulse-on time, and duty cycle for MRR, SR, and RLT. The best 21 solution sets predicted through the multi-objective optimization tool called non-dominated sorting genetic algorithm-II (NSGA-II) obeying the set objective functions are proposed which are obtained from the Pareto optimal frontiers. Accuracy levels of the predicted solution sets are verified by the confirmatory experiments showing the estimated errors of less than 10%. SEM analyses confirm excellent surface integrity with a comparatively thin recast layer formation.

Properties of millisecond-scale modulated pulsed power magnetron discharge applied for reactive sputtering of zirconia

The electrical properties of a modulated pulsed power (MPP) magnetron discharge were experimentally and theoretically studied in case of reactive sputtering of metallic zirconium target in argon/oxygen mixtures. The high-power pulsing was assisted by pre-ionization provided by a low-power direct current (DC) magnetron discharge filling the pulse-off period. The ranges of stable discharge operation parameters (applied voltage and oxygen flow rate) were determined for pulse-on time of 3 ms and pulse-off time 100–1000 ms. The maximum stable peak power density was 2.1 kW cm−2. Strong dependence of the MPP discharge current waveforms on the pulse-off time was found, indicating the important role of the pre-ionizing DC discharge. In presence of oxygen, discharge peak current was observed with characteristic width up to 1.5 ms, followed by non-reactive-like plateau region. For theoretical treatment of the observed discharge current behavior, we modified the well-known Berg model of reactive sputtering by introducing the terms required for adequate description of time-dependent poisoning and sputtering processes. The reactive ion implantation term was also transformed to account for the process saturation at high ion current densities. Calculation results from the modified Berg model demonstrated good agreement between our experimental observations of discharge current evolution and target poisoning dynamics in the timescale of milliseconds.

A study on Electrical Discharge Machining of Titanium Grade2 with experimental and theoretical analysis

Titanium alloys, due to their unique properties, are utilized in numerous modern high-end applications. Electrical Discharge Machining (EDM) is a non-conventional machining process, commonly used in machining of hard-to-cut materials. The current paper, presents an experimental study regarding the machining of Titanium Grade2 with EDM, coupled with the development of a simulation model. The machining performance indexes of Material Removal Rate, Tool Wear Ratio, and Average White Layer Thickness were measured and calculated for different pulse-on currents and pulse-on times. Moreover, the developed model that integrates a heat transfer analysis with deformed geometry, allows to estimate the power distribution between the electrode and the workpiece, as well as the Plasma Flushing Efficiency, giving an insight view of the process. Finally, by employing the Response Surface Methodology, educed regression models that correlate the machining parameters with the corresponding results, while for all the aforementioned indexes, ANOVA was performed.

Response Surface Modelling and Effective Application of Adaptive Neuro-Fuzzy Inference System to Analyze Surface Roughness of Al/Gr/Cp5 MMC Machined using WEDM

ABSTRACT This paper presents an investigation of wire electrical discharge machining (WEDM) of new fabricated aluminium base composite with 5% graphite by weight, i.e., Al/Gr/Cp5. The new fabricated metal matrix composite (MMC) has a complete application in space, defence, automobile, and other concerned metal industries. In this work, adaptive neuro-fuzzy inference system (ANFIS) and the response surface method (RSM) were selected for the analysis and modelling purposes. ANFIS is a soft computing technique used in nonlinear data training. Taguchi’s L27 plan was employed to conduct the experiments. The process parameters such as pulse-on time (PON), pulse-off time (POFF), a feed rate of wire (FRW) and the input current (IC) were selected for the experimentation. Based on the experimental findings, PON is identified as the most dominant parameter and the input current. WEDM performance was measured in terms of surface roughness (SR). For the optimised (minimum) surface roughness of 1.8625 microns, the best set of process parameters was PON (108 μs), POFF (52 μs), FRW (4 m/min) and the input current (12 Amp). ANFIS-predicted results were compared with the experimental results. An acceptable agreement is observed with the high value of the correlation coefficient (R2 = 0.9624). The soft computing technique, like ANFIS-RSM, shows a good competency and reliability for the presented work.

APPLICATION POTENTIAL OF RESPONSE SURFACE METHOD ON ELECTRO DISCHARGE MACHINING OF AA6061–CENOSPHERE AMCs PREPARED BY COMPOCASTING METHOD

Cenosphere fly ash particles are incorporated into AA6061 alloys with different concentrations ranging from 0[Formula: see text]wt.% to 10[Formula: see text]wt.% using a modified semi-solid metal processing technique. X-ray diffraction patterns were recorded to analyze the morphology of the aluminum-based metal matrix composites (AMCs). The major diffraction peaks of Al, SiO2, Al2O3 and Fe2O3 are distinctly identified which revealed the presence of cenosphere particles and their integrity within the matrix is preserved. The high-resolution optical micrograph identifies the homogeneous distribution and uniform dispersion of the particles. Machinability of the prepared AMCs was investigated by electro discharge machining (EDM) using response surface methodology (RSM). Face-centered CCD of RSM was considered to design the number of experimental runs required. ANOVA was used to explore the influence of selected process parameters and their interactions on the performance characteristics of the systems by developing a second-order quadratic mathematical model for all the responses. Pulse on-time and pulse current were observed to be the most influencing independent variables of EDM system that affect the selected performance measures during spark erosion process. Finally, desirability function approach was employed to optimize the parameters. The optimal processing condition was identified as follows: pulse current: 6 A, pulse on-time: 1010[Formula: see text][Formula: see text]s, percentage of reinforcement: 2% and flushing pressure: 0.2 MPa. Very small percentages of deviation have been observed while comparing with the experimental results obtained for MRR (8.6%), TWR (10.3%) and SR (2.18%).

Optimization of EDM Process Parameters on Machining Characteristics of SiC and Graphene Reinforced Al 6061-T6nano-Composites

Aluminum composites play an important role in various applications due to their low weight to strength ratio, high corrosive resistance, etc. As reinforcement materials, Graphene and SiCnano particles were used. Since, they havea high melting point, young modules, strong electrical and thermal properties etc. Electrical Discharge Machining (EDM) is one of the non-conventional machining techniques widely used for the machining of hard materials such as composites. The aim of current work is to evaluate the influence of EDM process parameters such as peak current, pulse on-time, voltage and flushing pressure on machining of Aluminium 6061 reinforced with 0.5 wt% SiC and 0.5 wt% Graphene nanoparticles. Al-based Metal Matrix Composite was casted by using liquid processing technique i.e. Stir Casting. Taguchi’s Design of Experiments was used to evaluate the effect of process parameters on machining characteristics i.e. Material Removal Rate (MRR) and Tool Wear Rate (TWR) of developed composite. From the results it was observed that peak current is the most influencing factor on MRR and TWR followed by other parameters.

Surface Integrity Enhancement of Incoloy 825 During Electric Discharge Machining

The aim of the current research work is to enhance the surface integrity of EDMed (electro-discharge machined) Incoloy 825 by suspending graphite powder particles in dielectric during electro-discharge machining (EDM). For this purpose, a specially designed and fabricated re-circulation dielectric tank was integrated with the existing EDM setup. The effect of three process variables, i.e., peak current, pulse-on time, and duty cycle was studied on EDM characteristics such as material removal rate, surface roughness (Ra), radial overcut, surface microhardness, microhardness in sub-surface regions, recast layer, phase changes and residual stress. Results showed that the machining rate increased up to 23% using powder-mixed EDM compared to conventional EDM. Significant reduction in surface roughness, white layer thickness, surface cracks and residual stress was observed while machining with graphite mixed dielectric. The addition of powder resulted in the formation of carbides and other alloy compounds on the machined surface which enhances the microhardness of surface and subsurface region.

Experimental investigation on EDM of Si3N4–TiN using grey relational analysis coupled with teaching-learning-based optimization algorithm

Electric discharge machining of silicon nitride–titanium nitride (Si3N4–TiN) ceramic composites was conceded for making square and circular profiles. Five imperative machining parameters namely current, pulse-on time, pulse-off time, dielectric pressure and spark gap voltage have been contemplated to resolve the response characteristics like material removal rate, electrode wear rate, surface roughness and geometrical tolerances. Multi Criteria Decision Making techniques like GRA and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are used to discover the optimal set of machining parameter combinations to accomplish maximum efficiency of all the responses. Also, Metaheuristic or nature inspired algorithm namely GRA coupled with TLBO algorithm is engaged for obtaining global optimum parameters. The parameters like the current, pulse-on time and spark gap voltage have the indicative impact on the responses like MRR, EWR and geometrical tolerances. It is acknowledged that the current and pulse-on time are most significant parameters among others. The optimal EDM parameters based on GRA and TOPSIS methods for obtaining better responses are current - 10 amps; pulse-on time - 8 μsec; pulse-off time - 4 μsec; dielectric pressure - 20 kg/cm2 and spark gap voltage - 32 V.

Application of ultrasound technology in the field of solid-state fermentation: increasing peptide yield through ultrasound-treated bacterial strain.

The increase of peptide yield contributed to reducing the usage of antibiotics in solid-state fermented feed. Ultrasound technology is used in the field of liquid-state fermentation to improve yield of fermented products but has not been utilized in the field of solid-state fermentation (SSF). The main objective of this study was to investigate the feasibility of improving peptide yield in SSF products through ultrasound-treated bacterial strain. The highest peptides content in soybean meal SSF products reached 153.28 mg g-1 , which increased by 15.05% compared with the control. This content value was acquired through treating the bacteria of Bacillus amyloliquefaciens by ultrasound before inoculating into soybean meal under the optimized mode and parameters (simultaneous dual-frequency ultrasound mode, frequency combination of 40/60 kHz, total power density of 40 W L-1 , time of 20 min, pulse-on and pulse-off times of 40 and 60 s, delayed inoculation time of 0 h). Fermenting with ultrasound-treated bacterial strain can effectively increase peptide yield, biomass and protease activity of soybean meal fermented products during the SSF prophase. After treating by ultrasound, the latent phase and logarithmic phase of the bacterial strain shortened by 1 and 3 h while the generation time reduced by 23.64%. In qualitative test of protease activity, diameter ratio (DR) value of ultrasound-treated bacterial cells enlarged by 12.0% compared with the control. Peptide yield of soybean meal SSF products can be improved through ultrasound-treated bacterial inoculum, which attributed to the promoting effect of ultrasound treatment on growth activity and protease production capability of bacterial cells. © 2021 Society of Chemical Industry.

A soft computing-based study on WEDM optimization in processing Inconel 625

This work presents an examination of the wire electric discharge machining (WEDM) in processing Inconel 625. The major WEDM variables (pulse-on time, pulse-off time, servo voltage, wire feed rate) were experimentally investigated to address multiple aspects of this process, namely to reduce the gap current and surface roughness and increase the cutting speed. After testing the statistical significance of the major WEDM parameters for the three responses, an advanced statistical procedure was utilized for tackling correlations among outputs and their integration into the WEDM output performance in a fully objective manner. The Bayesian regularized neural network established a highly accurate process model that was engaged as the objective function for the evolutionary algorithms to identify the optimal machining conditions. The following algorithms were employed: particle swarm optimization, teaching-learning based optimization, grey wolf optimization and Jaya algorithm. Their results were thoroughly analyzed in terms of accuracy, i.e., repeatability of the resulting solutions, convergence speed and computational time, including assessment of the hyperparameter effects. The obtained optimal solution was highly convincing and it was successfully validated in a confirmation run. Therefore, the benefits of these findings are twofold, offering: (i) a thorough analysis of the four metaheuristics effectiveness in dealing with a real industrial problem, (ii) useful insights for controlling WEDM variables to enhance the technological, environmental and economic aspects at the same time.

Impact of bubble coalescence in the determination of bubble sizes using a pulsed US technique: Part 2 – Effect of the nature of saturating gas

Knowledge on cavitation bubble size distribution, ambient radius of bubbles is of interest for many applications that include therapeutic and diagnostic medicine. It however becomes a hard quest when increasing the ultrasonic frequency, when direct observation of bubble dynamics is no longer possible. An indirect method based on the estimation of the bubble dissolution time under pulsed ultrasound (362 kHz) is used here under optimized conditions to derive ambient radii of cavitation bubbles in water saturated with He, Ar, Xe, O2, N2 and air: 3.0 µm for Ar, 1.2 µm for He, 3.1 µm for Xe, 2.8 µm for O2, around 1 µm for N2 and air. If the pulse on-time is increased, bubble coalescence occurs, the extent of which is rather limited for Ar but extremely high for He or N2.

Impact of bubble coalescence in the determination of bubble sizes using a pulsed US technique: Part 1 – Argon bubbles in water

A powerful experimental approach to measure the size distribution of bubbles active in sonoluminescence and/or sonochemistry is a technique based on pulsed ultrasound and sonoluminescence emission. While it is an accepted technique, it is still lacking an understanding of the effect of various experimental parameters, including the duration of the pulse on-time, the nature of the dissolved gas, the presence of a gas flow rate, etc. The present work, focusing on Ar-saturated water sonicated at 362 kHz, shows that increasing the pulse on-time leads to the measurement of coalesced bubbles. Reducing the on-time to a minimum and/or adding sodium dodecyl sulfate to water allows to reducing coalescence so that natural active cavitation bubble sizes can be measured. A radius of 2.9–3.0 µm is obtained in Ar-saturated water at 362 kHz. The effects of acoustic power and possible formation of a standing-wave on coalescence and measured bubble sizes are discussed.

Surface Modification Using Assisting Electrodes in Wire Electrical Discharge Machining for Silicon Wafer Preparation.

This paper outlines notable advances in the wire electrical discharge machining of polycrystalline silicon workpieces for wafer preparation. Our use of assisting electrodes permits the transfer of aluminum particles to the machined surface of the polycrystalline silicon workpieces, to enhance conductivity and alter surface topography regardless of the silicon’s crystallographic structure and diamond-type lattice. This in-process surface modification technique was shown to promote material removal and simultaneously preserve the integrity of the machined surfaces with preferable surface textures. In the validation experiment, the 25 mm-thick assisting electrodes deposited a notable concentration of aluminium on the machined surface (~3.87 wt %), which greatly accelerated the rate of material removal (~9.42 mg/s) with minimal surface roughness (Sa ~5.49 μm) and moderate skewness (−0.23). The parameter combination used to obtain the optimal surface roughness (Sa 2.54 μm) was as follows: open voltage (80 V), electrical resistance (1.7 Ω), pulse-on time (30 μs), and electrode thickness (15 mm). In multiple objective optimization, the preferred parameter combination (open voltage = 80 V, resistance = 1.4 Ω, pulse-on time = 60 μs, and assisting electrode thickness = 25 mm) achieved the following appreciable results: surface modification of 3.26 ± 0.61 wt %, material removal rate of 7.08 ± 2.2 mg/min, and surface roughness of Sa = 4.3 ± 1.67 μm.

Optimization of Parameters for Nitronic-60 on Wire-Cut Electrical Discharge Machining using Zinc-Coated Wire

The objectives of this work are to research the effective parameters of pulse ON time; pulse OFF time; voltage & wire feed whereas machined on Nitronic-60 exploitation wire-cut discharge machining exploitation zinc-coated wire. During this work, metal removal rate, surface roughness, and kerfwidth are taken as output parameters. The experimental results planned an optimum combination of parameters that provide the utmost material removal rate, minimum surface roughness, and kerf dimension. Finally, confirmation experiments were disbursed to spot the effectiveness of the planned technique. Multivariate analysis and ANOVA are performed exploitation Response Surface Linear Model.

Comparative Study of Electrical Discharge Machining, Electrical Discharge Drilling and Electrical Discharge Diamond Drilling of Nimonic 75

Due to wide range of applicability of hard and difficult-to-machine materials like super-alloys (Ti-alloys, Inconel, and Haste-alloy etc), advanced ceramics, composite materials, and high technical characteristics of above-mentioned materials, suitable advanced machining processes are conducted. EDM is one of the most popular advanced machining processes. But the EDM process has low metal removal rate (MRR) so EDD is another machining process as it has relatively higher MRR as compared to EDM. Here electric discharge diamond drilling (EDDD), a hybrid-EDM process comes into the picture in order to improve the machining performance characteristics. The present research aimed to compare the process performance in electrical discharge cutting, drilling and diamond abrasive drilling. The effects of process parameters such as peak current (I), pulse-on time (Ton), and pulse-off time (Toff) were studied on metal removal rate (MRR) and tool wear rate (TWR) in electrical discharge diamond drilling of Nimonic 75.

Determination of Multi-performance Characteristics in Electric Discharge Machining of DIN 1.2767 Steel Using Grey Relational Analysis


 Electric discharge machining (EDM) is one of the most important unconventional machining processes, which can cut hard materials and complex shapes that are difficult to machine by conventional machining processes easily and with high accuracy. In this study, L18 orthogonal array combined with gray relational analysis (GRA) is implemented to investigate the multiple performances characteristics in EDM of DIN 1.2767 Tool Steel. Machining process parameters selected were discharge current (Ip), pulse-on time (Ton), pulse-off time (Toff), and electrode material (copper alloys [NSS and B2]). The investigated performances characteristics were tool wear rate (TWR) and material removal rate (MRR). Analysis of variance (ANOVA) and Taguchi’s signal-to-noise ratio with the help of Minitab-17 software were used to analysis the effect of the process parameters on TWR and MRR. The experimental results and data analysis reveal that TWR and MRR are more affected by Ip and Ton. The minimum TWR was obtained at parametric combination Ip (6A), Ton (800 μs), and Toff (800 μs) and the maximum MRR attained at Ip (25A), Ton (800 μs), Toff (200 μs), and NSS electrode. After applying GRA, the optimal parametric combination for MRR and TWR was determined as Ip (25A), Ton (800 μs), Toff (200 μs), and NSS electrode. The study also exhibited the occurrence of an interaction between the variables on the responses. In addition, scanning electron microscopy images showed that the metal surface was affected with the increase in Ton and Toff.

Prediction of white layer formation in μ-WEDM process of NiTi shape memory superalloy: FEM with experimental verification

Microscopic changes in the surface of nickel-titanium (nitinol) shape memory alloys (SMAs) in micro-wire electro-discharge machining (μ-WEDM) due to the formation of a resolidified layer on the machined surface, called white layer, are one of the main drawbacks in the processing of such alloys. Since these changes significantly affect the shape memory and elastic recovery characteristics of these alloys, reduction of the white layer thickness (WLT) based on the selection of optimum process parameters is essential to raise the quality of the machined parts. In this regard, a finite element model (FEM) has been developed to simulate the effects of μ-WEDM process parameters, including discharge current, pulse on-time, pulse off-time, and servo voltage, on the heat distributing in Ni55.8Ti SMA to predict the WLT. The flushing efficiency of electric discharges and the effect of flow regime of the dielectric fluid on the heat distribution in the workpiece and the formation of the WLT are analyzed. Experimental data are used to verify the accuracy of the FEM. The results show that the developed model can predict the WLT in μ-WEDM process of Ni55.8Ti SMA with an average error of 14%. The effects of discharge parameters on the formation of the WLT are discussed in details based on the results of the FEM.

Variation of electrode materials and parameters in the EDM of an AA7075-TiO2 composite

Abstract The present study was carried out to analyze the effect of process parameters during EDM machining of AA7075-10 wt.-% TiO2 aluminum matrix composite (AMC). The composite was produced through stir casting. The EDM process parameters such as the electrode material (Cu, Br, EN-8), pulse current (5, 10 and 15 A), pulse ON time (300, 600 and 900 μs) and pulse OFF time (30, 60 and 90 μs) were chosen to study the effects on material removal rate, surface roughness and the electrode wear ratio. The experiment was carried out as per L27 orthogonal array based on Taguchi’s design of experiments. Signal-to-noise ratio and analysis of variance were used to identify the contribution of each input parameters on the output responses of the EDM process. The experimental results shows that pulse ON time and pulse current are the most significant factors for the material removal rate; pulse ON time and electrode material are the most influencing parameters for surface roughness and the electrode wear ratio.

Multiple-objective optimization of hydroxyapatite-added EDM technique for processing of 316L-steel

ABSTRACT Fabrication of the 316 L steel with moderate surface roughness (SR) and thin recast layer (RLT) is very difficult using both the conventional and non-traditional machining processes. Due to the stochastic behavior of electro-discharge machining (EDM) process, the machining performances significantly rely on the system variables. This research work aims to investigate the influences of EDM method variables on the machining performances during the machining of 316 L steel. Another goal is to minimize the performances by applying nano-hydroxyapatite (HA) particles in the EDM-Oil. Moreover, the optimal solutions for processing of 316 L through the NSGA-II method are proposed in this research. Followed by the pulse-on time and HA amount, ANOVA study reports peak current being the most important parameter for the responses such RLT and SR. The augment of peak current, HA amount, and pulse-on time result comparatively lower RLT and SR than the previous studies. The best 7 solutions selected from the predicted 120 solutions following the objectives are proposed generating the Pareto frontiers. Less than 10% of the validation tests errors confirm the high accuracy of the predicted solutions. The present research proposed a potential and cost-effective method for processing of 316 L steel.