Investigation of the Effect of Process Parameters on Surface Roughness in Wire EDM of Titanium Alloy

2012 ◽  
Vol 472-475 ◽  
pp. 78-81 ◽  
Author(s):  
Mohinder Pal Garg ◽  
Ajai Jain ◽  
Gian Bhushan
Keyword(s):  
Surface Roughness ◽  
Water Pressure ◽  
Peak Voltage ◽  
Peak Current ◽  
Wire Breakage ◽  
Pulse Peak ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Time Pulse

This paper investigates the Wire Electric Discharge Machining of Titanium alloy 6-2-4-2.Eight process parameters namely pulse-on time, pulse-off time, peak current, spark gap set voltage, wire feed, wire tension, water pressure, pulse peak voltage and servo feed are varied to study their effect on surface roughness and wire breakage. The experiments are conducted using one-factor-at-a-time approach. Moreover, a few random experiments are also carried to study the phenomenon of wire breakage precisely. The study revealed that surface roughness is directly affected by the pulse-on time, pulse-off time, peak- current, spark gap set voltage and wire tension. Wire feed, Water pressure and pulse peak voltage have negligible effect on the surface roughness. Moreover, wire breakage is predominantly dictated by all the parameters except peak current and pulse peak voltage. An optimum range of input parameters has been bracketed as the final outcome for cutting in terms of surface roughness and to minimize the wire breakage frequency.

scholarly journals Findings of performance evaluation of EDM for different materials of electrodes and work pieces- a review

2018 ◽  
Vol 7 (4.5) ◽  
pp. 542
Author(s):  
Harshalkumar R. Mundane ◽  
Dr. A. V. Kale ◽  
Dr. J. P. Giri
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Performance Measure ◽  
Machining Process ◽  
Machining Parameters ◽  
Spark Erosion ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Time Pulse

EDM (Spark erosion) is non-conventional machining process which uses as removing unwanted material by electrical spark erosion. EDM Machining parameters affecting to the performance and the industries goal is to produce high quality of product with less time consuming and cost. To achieve these goals, optimizing the machining parameters such as pulse on time, pulse off time, cutting speed, depth of cut, duty cycle, arc gap, voltage etc. The performance measure of EDM is calculated on the basis of Material Remove Rate(MRR), Tool Wear Rate(TWR), and Surface Roughness(SR).The main objective of present work is to investigate of the influence of input EDM (Electro Discharge Machining) parameters on machining characteristics like surface roughness and the effects of various EDM process parameters such as pulse on time, pulse off time, servo voltage, peak current, dielectric flow rate, on different process response parameters such as material removal rate (MRR), surface roughness (Ra), Kerf (width of Cut), tool wear ratio(TWR)and surface integrity factors. In this paper few selected research paper related to Die-sinker EDM with effect of MRR, TWR, surface roughness (SR) and work piece material have been discussed.   

A Comparison of the Effects of Wire Electrical Discharge Machining Parameters on the Processing of Traditionally Manufactured and Additively Manufactured 316L Stainless Steel Specimens

2018 ◽  
Author(s):  
Gregory Bicknell ◽  
Guha Manogharan
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
316L Stainless Steel ◽  
Machining Parameters ◽  
Wire Edm ◽  
Machining Time ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Time Pulse

Wire electric discharge machining (EDM) is a non-traditional machining method that has the ability to machine hard, conductive materials, with no force and high precision. This technology is used in industries, like the aerospace industry, to create precision parts used in high stress applications. Wire EDM is also commonly used in additive manufacturing (AM) applications to remove printed parts from the base-plates onto which they are printed. Numerous studies show the effects of EDM parameters, like pulse-on time, pulse-off time, and cutting voltage, on the processing of traditionally fabricated metal parts. However, very few studies identify how the parameters of wire EDM affect the processing of AM parts. This paper studies the effect of wire EDM pulse-on time, pulse-off time, and cutting voltage on the machining time, surface roughness, and hardness of additively manufactured 316L stainless steel cylinders. The effects of these wire EDM parameters are then tested on the machining time, surface roughness, and hardness of wrought 316L stainless steel cylinders. It was found that machining time of AM samples was statistically significantly lower than wrought samples and also had better surface finish and lower surface hardness.

scholarly journals Parametric Study of Machining on EN31 and EN19 Alloy Steels in WEDM to Analyze the Effect on Surface Roughness

2018 ◽  
Vol 7 (2) ◽  
pp. 36-42
Author(s):  
Ramandeep Singh ◽  
Ashok Kumar
Keyword(s):  
Surface Roughness ◽  
Input Parameter ◽  
Hard Materials ◽  
Current Voltage ◽  
Alloy Steels ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Wire Feed ◽  
Time Pulse

Wire EDM can machine hard materials as well as alloys. Thus this study aims to analyze the effect of process parameters in WEDM on EN31 and EN19 alloy steels. The parameters selected for the optimization were Work material, Pulse on Time, Pulse off Time, Current, Voltage and Wire Feed for improvement in surface roughness. Taguchi L18 Orthogonal array was used for the best combination of experiment. The output responses were analyzed by ANOVA (Analysis of variance). The ANOVA result indicated that there is a significant effect on improvement in surface roughness when machining with all these six input parameter and coated wire. According to the present investigation, voltage was found to be the most significant factor followed by Ton and current, which affect the improvement in surface roughness.

Application of Machine Learning Techniques for Multi Objective Optimization of Response Variables in Wire Cut Electro Discharge Machining Operation

2019 ◽  
Vol 969 ◽  
pp. 800-806
Author(s):  
Sidharth Kumar Shukla ◽  
Amrita Priyadarshini
Keyword(s):  
Machine Learning ◽  
Surface Roughness ◽  
Gradient Descent ◽  
Descent Method ◽  
Kerf Width ◽  
Gradient Descent Method ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Time Pulse

Wire Cut Electrical Discharge Machining (WEDM) is a non-conventional thermal machining process which is capable of accurately machine alloys having high hardness or part having complex shapes that are very difficult to be machined by the conventional machining processes. The WEDM finds applications in automobiles, aero–space, medical instruments, tool and die industries, etc. The input parameters considered for WEDM are pulse on time, pulse off time, flushing pressure, servo voltage, wire feed rate and wire tension. Performance of WEDM is mainly assessed by output variables such as, material removal rate (MRR), kerf width (Kw) and surface roughness (Ra) of the work piece being machined. Looking at the need of a suitable optimization model, the present work explores the feasibility of machine learning concepts to predict optimum surface roughness and kerf width simultaneously by making use of experimental data available in the literature for machining of Hastelloy C– 276 using WEDM. In most of the literatures, single objective optimization has been carried out for predicting optimum cutting parameters for WEDM. Hence, the present work presents a methodology that makes use of a machine learning algorithm namely, gradient descent method as an optimization technique to optimize both surface roughness and kerf width simultaneously (multi objective optimization) and compare the results with the existing literatures. It was observed that the input parameters such as pulse on time, pulse off time, and peak current have significant effect on both surface roughness and kerf width. The gradient descent method was successfully used for predicting the optimum values of response variables.

Experimental Investigation of Process Parameters in Wire Electrical Discharge Machining by Response Surface Methodology on IS2062 Steel

2014 ◽  
Vol 550 ◽  
pp. 53-61
Author(s):  
R.Arun Bharathi ◽  
P.Ashoka Varthanan ◽  
K. Manoj Mathew
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Machining Parameters ◽  
Peak Current ◽  
Custom Design ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time

The objective of the present work is to predict the optimal set of process parameters such as peak current (IP), pulse on/off time (TON/TOFF) and spark gap voltage (SV) to achieve minimum Surface roughness (Ra), wire consumption rate (WCR) and maximum material removal rate (MRR). In this work, experiments were carried out by pulse arc discharges generated between ZnO coated brass wire and specimen (IS2062 steel) suspended in deionized water dielectric. The experiments were designed based on the above mentioned four factors, each having three levels. Custom design based Response Surface Methodology (RSM) is used in this research. 21 runs of experiments were constructed based on custom design procedure and results of the experimentation were analyzed analytically as well as graphically. Moreover the surface roughness after machining was measured by Taylor Hobson Surtronic device. Second order regression model has been developed for predicting Ra, WCR and MRR in terms of interactive and higher order machining parameters through RSM, utilizing relevant experimental data as obtained through experimentation. The research outcome identifies significant parametersand their effect on process performance on IS2062 steel. The results revealed that peak current, pulse on-time and their interactions have significant effects on Ra, whereas pulse off time and peak current have significant effects on MRR and it is also observed that peak current and interaction between peak current and pulse off time have significant effects on WCR. The adequacy of the above proposed models has been tested through the analysis of variance (ANOVA).

scholarly journals Evaluation of machining performance and multi criteria optimization of novel metal-Nimonic 80A using EDM

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Vikas K. Shukla ◽  
Rakesh Kumar ◽  
Bipin Kumar Singh
Keyword(s):  
Surface Roughness ◽  
Removal Rate ◽  
Minimum Energy ◽  
Process Parameter ◽  
Simultaneous Action ◽  
Peak Current ◽  
Nimonic 80A ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time

AbstractThis study focused to machine novel Nimonic 80A through Electric Discharge Machine process. The process parameters are optimised to achieve high surface integrity along with high material removal rate (MRR) with minimum energy consumption. Central composite design along with analysis of variance technique has been applied to make correlation between the process parameter and responses. The developed model of surface roughness shows that the peak current and pulse-on time have significant effect whereas; a little effect of pulse-off time. The said result may be obtained due to simultaneous action of deposition and notching (removal) of material in order to form crater. In case of MRR, the pulse-on time and peak current are found as significant factors with increasing trend (i.e. when the input values are increased the MRR increases) whereas; a reverse trend is noticed with pulse-off time. The optimum values for maximum MRR (0.512444 gm/min) and minimum surface roughness (7.82203 µm) with 81% desirability are obtained for the process parameter as 13.49 A peak current, 150 µs pulse-on time and 4 µs pulse-off time.

A Study on Surface Roughness and Cutting Width for Circular Contour Machining of Stir Cast AA6063/SiC Composites in WEDM

2017 ◽  
Vol 13 (10) ◽  
pp. 6524-6530
Author(s):  
I. Balasubramanian
Keyword(s):  
Surface Roughness ◽  
Electrical Discharge Machining ◽  
Stir Casting ◽  
Circular Contour ◽  
Sic Composites ◽  
Contour Machining ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Time Pulse

Wire electrical discharge machining is used in machining electric conductive materials with intricate shapes and profiles. This paper presents an experimental investigation on the influence of cutting conditions of WEDM on surface roughness and cutting width of machining of AA6063/SiC composites. Here a semi cylindrical piece is removed from a rectangular plate of AA6063/SiC composites plate fabricated with reinforcing SiC in 0%, 5%, 10% and 15% weight fractions through stir casting. The effect of WEDM parameters such as pulse on time, pulse off time and peak current on surface roughness and cutting width on different composition of AA6063/SiC were analyzed for circular contour machining. The experimental results show that increase in percentage of SiC has high influence in mechanical behavior of AA6063/SiC composites and the effect of pulse on time is very significant in reducing the surface roughness and pulse off time plays an important role in producing minimum cutting width.  

Surface Quality Produced in EDM with Tungsten Carbide and Copper Compacted Electrodes

2015 ◽  
Vol 1115 ◽  
pp. 24-28 ◽  
Author(s):  
Ahsan Ali Khan ◽  
Mohammed Baba Ndaliman ◽  
Ummu Atiqah Khairiyah binti Mohamad ◽  
Nurul Farhana binti Sulong ◽  
Zakaria Mohd Zain
Keyword(s):  
Surface Roughness ◽  
Electrical Discharge Machining ◽  
Surface Hardness ◽  
Machining Performance ◽  
Peak Current ◽  
Work Surface ◽  
Machining Conditions ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time

Electrical discharge machining (EDM) is one of the most commonly used technique to machine very hard materials. Materials like hardened tool steels, titanium and its alloys and difficult-to-machine materials can be easily processed with EDM. The machining performance to a great extent depends on the composition of the electrode. This paper presents the machining performance of powder metallurgy (PM) compacted electrodes made from titanium carbide (TiC) and copper (Cu) powders. The Cu-TiC electrodes made up of 70% of TiC and 30% of Cu powders. They were compacted at a pressure of 6,000 psi (41.34 MPa). Mild steel was used as the workpiece material. Machining was conducted with the peak current, pulse-on time and pulse-off time as the electrical input variables. The output variables of the investigation were work surface roughness and its hardness. It was found that work surface roughness increases with increase in current and pulse-on-time. However, it decreases with increase in pulse-off time. It was found that the highest value of surface roughness (14.782 μm) was found at highest peak current (6.5 A), highest pulse on-time (7.5 μs) and lowest pulse-off time (6.5 μs). The highest value of surface hardness (57.3 BHB) was found at the same machining conditions. The smoothest surface (14.782 μm) was found at the lowest peak current (3.5 A), lowest pulse on-time (6.0 μs) and highest pulse-off time (8.5 μs). The lowest value of surface hardness (42.9 BHB) was found at the same machining conditions.

Investigation of Surface Roughness for Inconel 718 in Blind Hole Drilling with Rotary Tool Electrode

2019 ◽  
Vol 18 (03) ◽  
pp. 379-394
Author(s):  
Rakesh Kumar ◽  
Anand Pandey ◽  
Pooja Sharma
Keyword(s):  
Surface Roughness ◽  
Inconel 718 ◽  
Work Piece ◽  
Tool Electrode ◽  
Tool Diameter ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Tool Rotation ◽  
Off Time ◽  
Time Pulse

The research investigation reported on the effect of machining parameters on surface roughness (Ra) in electric discharge drilling of Inconel 718. Machining was done by using a copper tool electrode. Machining was conducted by considering different process parameters viz. tool diameter, discharge current, pulse on time, pulse off time, tool rotation and depth of hole. Optical surface profiler was used to measure surface roughness of drilled hole in work-piece. Design of experiment was created by Taguchi method based L18 orthogonal array. For minimum surface roughness, optimum parameters were found using Analysis of variance (ANOVA). Based on analysis, it is found that pulse off time, pulse on time and tool rotation are the most significant parameters that affect the surface roughness. Tool diameter is the less significant parameter that affects the surface roughness. Regression analysis was used to predict a value for minimum surface roughness. The scanning electron microscope (SEM) images were used to identify the microstructure of the drilled hole in Inconel 718 work-piece. Interaction plots and residual plot have been plotted for surface roughness to identify the interaction between parameters and residual errors, respectively.

HYBRID MODELING OF PROCESS PARAMETERS PRODUCED BY ELECTRIC DISCHARGE MACHINING USING DIFFERENTIAL EVALUATION AND PARTICLE SWARM OPTIMIZATION

2013 ◽  
Vol 12 (02) ◽  
pp. 147-169
Author(s):  
R. RAJESH ◽  
M. DEV ANAND
Keyword(s):  
Heat Resistance ◽  
Discharge Voltage ◽  
Machining Parameters ◽  
Peak Current ◽  
Spark Gap ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Edm Process ◽  
Time Pulse

One of the important advanced manufacturing technologies in machining hard-to-cut complicated contour is electrical discharge machining (EDM) and it is highly appreciated because it is economical and effective for moulding materials of heat resistance and high strength into complex one. The EDM process deals with erosion of electrically conductive materials by the way of initiating rapid and repetitive spark discharge between the work piece and electrode tool, with the separation of gap of 0.05 to 0.5 mm which is called spark gap. A die electric fluid soakes this spark gap. In EDM process machining parameters are considered to be important to achieve optimal machining performance in high heat resistance and hard material. The hand book provides all the details about the opted machining parameters but it does not guarantee that the obtained parameters are close to optimal performance. The EDM process should have the features of robustness, accuracy, process capability to confront with the challenges of the changing world. The EDM process should be modeled and optimized to achieve perfection as mentioned above. The researcher uses RSM to investigate the effect of five controllable input variables (viz) peak current, discharge voltage, pulse on time, pulse off time, and oil pressure. MRR and SR, two output variables are the responses. Experiments were administered on AISI 1020 steel with copper electrode. The response is modeled using RSM on experimental data. The remarkable coefficients are received by performing analysis of variance (ANOVA) at the level of 5%. This study shows the MRR and SR have been significantly influenced by peak current, pulse on time, pulse off time, discharge voltage and oil pressure. The soft computing tools differential evolution and PSO are framed, developed, experimented as predictive models.

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