Multi-objective parametric optimization on machining with wire electric discharge machining

Wire Electrical Discharge Machining (WEDM) is a versatile process to generate intricate and complex shapes on conductive work material with high dimensional accuracy and surface finish. Since the process is stochastic, its input parameters play critical role for achieving desired accuracy and precision of the component. Inconel 718, High-Strength-Temperature-Resistant (HSTR) material, has wide applications in the field of aerospace, automobile, mould making and medical industries. Hence, machining of Inconel 718 using WEDM is a challenging task. Also experimentation on Inconel 718 with WEDM is costly as well as time consuming process. Therefore to study the behavior of WEDM process with different process parameters for effective and efficient operation, process modeling and simulation using appropriate software is highly essential. In the present investigation, a 3-D single spark finite element thermal model for WEDM process has been developed using ANSYS software. This model has some more realistic assumptions like heat flux following Gaussian distribution and spark radius as a function of time and energy. Plasma incident region is meshed by keeping elemental size equal to one tenth of entire plasma radius, so that exact ten elements can be fitted. Identified elements were thermally loaded by applying element wise different temperatures for getting more accurate temperature distribution profile. This profile was found to be having crater shape matching with earlier Finite Element Models (FEM) available in the literature. Along with the shape, it also helps to decide the elements having temperatures greater or equal to melting point leading to estimate Material Removal Rate (MRR). Later on single spark MRR can be used to estimate multi-discharge-MRR by calculating pulse rate. Model MRR is validated with the experimental MRR which show a very good agreement, but little variation. This variation in the modeling could possibly due to assumptions like no delay in ignition, non-deposition of recast layer (100% flushing efficiency), etc. The factors like incomplete flushing of debris and inter-electrode gap arcing cause the variation in machining conditions thus reducing the actual MRR. In the present investigation, the use of dielectric is considered only for convection, but in reality, it acts as an insulator, coolant and also as debris remover. Melting and vaporization of material is the main phenomena for material removal. Dielectric fluid partially removes the molten metal because at the same time, the molten metal is under very high pressure due to plasma channel. Its adhesive property resists the material removal. It is very difficult to incorporate all real effects in the model, however the obtained results in the present study show good agreement between model MRR and experimental MRR within 10% variation.

The effect of heterogeneous second phase on the machinability evaluation of spheroidal graphite cast irons in the WEDM process

This article reports about analysis and optimization of surface roughness parameters (i.e. average roughness Ra and maximum roughness Rt) of wire electrical discharge machined fine-pitch miniature spur gears made of brass. Effects of four wire electrical discharge machining process parameters (i.e. voltage, pulse-on time, pulse-off time and wire feed rate) on the surface roughness parameters of the miniature gears were studied by conducting 29 experiments with two replicates each and designed based on Box–Behnken approach of response surface methodology. Analysis of variance study found all four input parameters to be significant. Experimentally, the surface roughness has been found to increase with higher voltage and longer pulse-on time and decrease with longer pulse-off time and higher wire feed rate. Desirability analysis was used to optimize the wire electrical discharge machining parameters, so as to minimize the Ra and Rt simultaneously. Optimum values of Ra and Rt obtained from the confirmation experiments conducted at the optimized wire electrical discharge machining parameters are superior than the values reported in the literature. Artificial neural network model has been developed for prediction of the surface roughness of the wire electrical discharge machined miniature gears. Very close agreement was found among the surface roughness values predicted by response surface methodology and artificial neural network with the corresponding experimental values.

Shape memory alloy (SMA), particularly those having a nickel–titanium combination, can memorize and regain original shape after heating. The superior properties of these alloys, such as better corrosion resistance, inherent shape memory effect, better wear resistance, and adequate superelasticity, as well as biocompatibility, make them a preferable alloy to be used in automotive, aerospace, actuators, robotics, medical, and many other engineering fields. Precise machining of such materials requires inputs of intellectual machining approaches, such as wire electrical discharge machining (WEDM). Machining capabilities of the process can further be enhanced by the addition of Al2O3 nanopowder in the dielectric fluid. Selected input machining process parameters include the following: pulse-on time (Ton), pulse-off time (Toff), and Al2O3 nanopowder concentration. Surface roughness (SR), material removal rate (MRR), and recast layer thickness (RLT) were identified as the response variables. In this study, Taguchi’s three levels L9 approach was used to conduct experimental trials. The analysis of variance (ANOVA) technique was implemented to reaffirm the significance and adequacy of the regression model. Al2O3 nanopowder was found to have the highest contributing effect of 76.13% contribution, Ton was found to be the highest contributing factor for SR and RLT having 91.88% and 88.3% contribution, respectively. Single-objective optimization analysis generated the lowest MRR value of 0.3228 g/min (at Ton of 90 µs, Toff of 5 µs, and powder concentration of 2 g/L), the lowest SR value of 3.13 µm, and the lowest RLT value of 10.24 (both responses at Ton of 30 µs, Toff of 25 µs, and powder concentration of 2 g/L). A specific multi-objective Teaching–Learning-Based Optimization (TLBO) algorithm was implemented to generate optimal points which highlight the non-dominant feasible solutions. The least error between predicted and actual values suggests the effectiveness of both the regression model and the TLBO algorithms. Confirmatory trials have shown an extremely close relation which shows the suitability of both the regression model and the TLBO algorithm for the machining of the nanopowder-mixed WEDM process for Nitinol SMA. A considerable reduction in surface defects owing to the addition of Al2O3 powder was observed in surface morphology analysis.

Study on the movement of wire electrode during fine wire electrical discharge machining process

Engineering industry has made tremendous growth in its manufacturing fields in the last decade but still the modern machines are not utilized up to the desired level. Wire electrical discharge machining (WEDM) is one such sophisticated machining process used in industry, which is a high-speed cutting and high-precision machining to realize productivity and improved accuracy for all manufacturing parts. Optimisation of the operating parameters of WEDM will result in efficiency with regard to higher surface finish and maximum material removal rate. The present investigation of the cutting performance on die steel with different parameters such as pulse on time, pulse off time, servo voltage, wire feed, current and cutting speed were involved to determine by which using wire electric discharge machining(WEDM) process. The shape of the wire and base material dimensions of brass wire 0.25mm diameter and AISI D2 steel with 100× 100 × 10 mm were carried out. The cutting performance outputs considered in this study are material removal rate (MRR), Kerf width and surface roughness (Ra). Experiments were carried out under Taguchi's L16 orthogonal array under different conditions of parameters. An optimal combination of WEDM parameters for proper machining of AISI D2 steel to achieve better surface roughness and Materials Removal Rate (MRR) is achieved in this investigation.

Wire EDM process parameter optimization for D2 steel

PurposeAn experimental study has been conducted to model and optimize wire electric discharge machining (WEDM) process parameters such as pulse-on time, pulse-off time, servo voltage and peak current for response characteristics during machining of Nimonic 75 alloy.Design/methodology/approachThe response surface methodology (RSM)-based Box–Behnken's design has been employed for experimental investigation. RSM is used for developing quadratic regression models for selected response variables i.e. material removal efficiency and kerf width. To validate the model, confirmation experiments have been performed. The multi-response optimization has been done using desirability function approach.FindingsThrough analysis of variation, the percent contribution of process parameters on the response characteristics has been found. Pulse-off time is the most significant parameter affecting the kerf width and material removal efficiency followed by pulse-on time. The quadratic regression models have been developed for prediction of selected response variables. An attempt has been made to optimize the WEDM parameters for material removal efficiency and kerf width. The recommended process parameter setting for maximum material removal efficiency and minimum kerf width have been found to be pulse-on time = 0.6 µs, pulse-off time = 14 µs, servo voltage = 25 V and peak current = 200 A.Originality/valueThe “kerf width” is an important response variable for maintaining dimensional accuracy of the machined component, but has not been given due attention by the researchers. In the present work, the developed regression model for “kerf width” can be used in estimating wire offset setting and thereby getting a dimensionally accurate product. The optimum process parameters obtained in WEDM of Nimonic 75 alloy will contribute in database of machining. The outcome of this study would be added to scare database of the machining of Nimonic 75 alloy and also would be extremely useful for making the technology charts for WEDM.

An investigation of material removal rate and surface roughness of squeeze casted A413 alloy on WEDM by multi response optimization using RSM

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 ( T on ), pulse-off time ( T off ) and peak current ( I p ) 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 mm 3 /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 ( T on = 40µs, T off = 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 R a values. ANOVA results stated that T on has contributed 20.4%, 35.8% and 19.3%, and I p 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 mm 3 /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 ( R sk = −0.274) and at highest level showed a larger deviation in skewness ( R sk = +2.672) signifies that higher asymmetry (poor) of the surface.

Metal matrix composites have become a vital concern for the modern manufacturing companies due to some of their special properties. The presence of reinforcement makes them difficult in machining operations to achieve industrial requirements. Therefore, it is necessary to optimize the machining process parameters to improve output performance in terms of product quality. The overall performance of the wire electrical discharge machining (WEDM) process is influenced by various parameters, such as pulse-on time, pulse-off time, induced current, and wire-feed. WEDM is one of the non-traditional machining processes. It machines only electrically conducting materials and machines the surfaces by the thermo-electrical process. During machining of composites, material removal rate, cutting speed, and surface roughness have been considered for this research. The relation between the process parameters and the output responses is developed by using linear regression analysis through Minitab-17. The experiments conducted are dependent on Taguchi $${\hbox {L}}_{25}$$ orthogonal array. The optimized sets of process parameters are obtained by using teaching and learning-based optimization.

The present work emphasis on behavior of zinc-aluminium alloy reinforced with silicon carbide particles when machined with wire electric discharge machining process (WEDM). The difficulty faced by conventional machining is severe tool damage while machining metal matrix composites. Electrical discharge machining can be successfully employed for machining MMC in the place of conventional machining to reduce the tool damage and to produce complicated contours with superior finish. In the present study ZA43 reinforced with SiCp is machined by wire EDM process. Machining is carried-out by varying applied current of (2, 4 and 6amp.), pulse on time (4, 8 and 16μs) and pulse off time (5, 7 and 9μs) while other parameters such as voltage, dielectric flushing pressure, wire tension etc. are maintained constant. It is observed that reduction in the material removal rate and increase in surface roughness for increasing reinforcement percentage in the composite. It is also observed that applied current and pulse on time increases the material removal rate where as pulse off time has less effect on it.

Tungsten carbide-cobalt composite (WC-Co) is commonly considered a difficult to machine material due to its very high hardness. High strength and wear resistance make WC-Co a preferred material for manufacturing of tools, dies, and molds, etc. All such applications require complex shapes to be machined including curved features. The present study is carried out to evaluate the potential of wire electric discharge machining (WEDM) to fabricate concave and convex curved profiles of different radii in WC-Co. Taguchi design of experiments technique has been employed to investigate the influence of six control variables including open circuit voltage, pulse-on time, pulse-off time, servo voltage, wire tension, and dielectric pressure, on two response characteristics namely radius of concave profile and radius of convex profile. The analysis of variance (ANOVA) has been performed to identify the significant parameters affecting the performance measures. Regression models have also been developed for both profiles to predict the radii of curved profiles against any combination of machining parameters. It has been observed that machining performance in terms of overcut and undercut depends on the geometry to be machined. However, proposed combinations of machining parameters could effectively reduce undercut/overcut of the profiles to 10 μm. Moreover, scanning electron microscopy has been performed in order to visualize recast layer, micro-cracks, and micro-chipping caused by WEDM process.

Non-traditional machining methods like wire electric discharge machining (WEDM) appear to be an ideal choice for machining high strength super alloys like Inconel 706, because of their capability to generate intricate profiles with high accuracy. However, wire breakages are a common problem in the WEDM process and adversely affect the productivity, accuracy, and surface quality. Therefore, the aim of this work is to investigate and comprehend the phenomenon of wire breakage using Inconel 706 as work material and brass wire, diffused brass wire, and zinc-coated brass wire as electrode materials. Six process parameters—pulse-on time, pulse-off time, peak current, spark gap voltage, wire feed rate, and wire tension—have been varied experimentally to determine their effect on the frequency of wire failure. According to the findings, the zinc-coated brass wire breaks with the lowest frequency when compared to the other two. Additionally, an ideal range of input variables has been proposed for efficient WEDM of Inconel 706 without unexpected wire breakages. This range can also be utilized for further research work related to modeling and optimization in WEDM of Inconel 706.

Studies are made on the wire electrical discharge machining (WEDM) process performance parameters such as material removal rate, kerf and surface roughness of Incoloy®Alloy800 following the Taguchi’s design of experiments. ANOVA is performed to trace the statistically significance of input parameter (viz. gap voltage, pulse-on-time, pulse-off-time and wire feed) on the WEDM process parameters. A simple multi-objective optimization approach is suggested for specifying a set of optimum input parameters to achieve maximum material removal rate, and minimum surface finish and kerf width.