scholarly journals Multi-Objective Optimization of Wire Electro Discharge Machining (WEDM) Process Parameters Using Grey-Fuzzy Approach

2018 ◽  
Vol 63 (1) ◽  
pp. 16-25 ◽  
Author(s):  
Partha Protim Das ◽  
Sunny Diyaley ◽  
Shankar Chakraborty ◽  
Ranjan Kumar Ghadai
Keyword(s):  
Process Parameters ◽  
Removal Rate ◽  
Machining Process ◽  
Wire Tension ◽  
Electro Discharge Machining ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Fuzzy Logic Technique ◽  
Off Time

Wire electro discharge machining (WEDM) is a versatile non-traditional machining process that is extensively in use to machine the components having intricate profiles and shapes. In WEDM, it is very important to select the optimal process parameters so as to enhance the machine performance. This paper emphasizes the selection of optimal parametric combination of WEDM process while machining on EN31 steel, using grey-fuzzy logic technique. Process parameters such as servo voltage, wire tension, pulse-on-time and pulse-off-time were considered while taking into account several multi-responses such as material removal rate (MRR) and surface roughness (SR). It was found that pulse-on-time of 115 µs, pulse-off-time of 35 µs, servo voltage of 40 V and wire tension of 5 kgf results in a larger value of grey fuzzy reasoning grade (GFRG) which tends to maximize MRR and improve SR. Finally, analysis of variance (ANOVA) is applied to check the influence of each process parameters in the estimation of GFRG.

scholarly journals PSI and TOPSIS Based Selection of Process Parameters in WEDM

2017 ◽  
Vol 61 (4) ◽  
pp. 255 ◽  
Author(s):  
Sunny Diyaley ◽  
Pramod Shilal ◽  
Ishwer Shivakoti ◽  
Ranjan Kumar Ghadai ◽  
Kanak Kalita
Keyword(s):  
Tool Steel ◽  
Process Parameters ◽  
Machining Process ◽  
Wire Tension ◽  
Input Parameters ◽  
The Wire ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Selection Of

Wire electric discharge machining (WEDM) is a nontraditional machining process for machining conductive materials with complex and intricate shapes with a high surface finish and dimensional accuracy. The decision making for the selection of the best set of combinations of input process parameters is a major challenge. Therefore a proper optimization tool should be used for the optimal selection of process parameters. The resent work deals with the comparative study of Preferential Selection Index (PSI) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for the selection of process parameters during machining of EN31 tool steel. Four input parameters- Pulse on Time (Ton ), Pulse off Time (Toff  ), Servo Voltage (SV) and the Wire tension (WT) are considered. Surface roughness and material removal rate are the measured output responses. Taguchi L9 orthogonal array is used for developing the experimental design. Three levels of each control factor are considered. The results show that a single parameter alone does not have a significant influence on the output responses. Thequality of the output responses depends on the combination of the various set of input parameters. The best set of combination suggested from the current input parameters for machining of EN31 Tool Steel by Wire EDM Process is found to be Pulse on Time (Ton )= 15μs, Pulse Off Time (Toff  )=35μs, Servo Voltage (SV)=40V and the Wire tension (WT)=5kgf from both PSI as well as TOPSIS techniques. Confirmation experiments are performed to validate the optimal results.

scholarly journals Experimental investigation for the effects of wire EDM process parameters over the tapered cross-sectional workpieces of titanium alloys (Ti6Al-4V)

2020 ◽  
Vol 11 (1) ◽  
pp. 221-232
Author(s):  
Muhammad Wasif ◽  
Syed A. Iqbal ◽  
Anis Fatima ◽  
Saima Yaqoob ◽  
Muhammad Tufail
Keyword(s):  
Process Parameters ◽  
Removal Rate ◽  
Cross Sectional ◽  
Electro Discharge Machining ◽  
Controllable Factors ◽  
Roughness Analysis ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Off Time ◽  
Response Variables

Abstract. The main purpose of this research is to examine the outcomes of process parameters of Wire Electro-discharge Machining over the tapered workpieces of Titanium Alloy (Ti6Al-4V). Taper angle, current and pulse-off time are considered as the controllable factors effecting the response variables. Each sample has been cut with varying sets of machine controllable parameters to assess their effect on response variables; kerf width, wire wear, Material Removal Rate and surface roughness. Analysis of variances is applied, and mean Reponses are determined to recognize and compare the most influencing parameters over the response variables for the WEDM Process. Regression model for the response variables are also developed using which optimized WEDM process parameters are determined for the optimal response variables. It can be concluded that varying thickness of materials due to tapered cross section affects all the four-response variable, while, current and pulse-off time along with their interactions have high impact over the response variables.

Identification of Optimal Process Parameters in Electro-Discharge Machining Using ANN and PSO

2018 ◽  
pp. 72-90 ◽  
Author(s):  
Kaushik Kumar ◽  
J. Paulo Davim
Keyword(s):  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Machining Process ◽  
Repair Work ◽  
Electro Discharge Machining ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Edm Process ◽  
Time Pulse

Electrical Discharge Machining (EDM) process is a widely used machining process in several fabrication, construction and repair work applications. Considering Pulse-On Time, Pulse OFF time, Peak-Current and Gap voltage as the inputs and among all possible outputs, in the present work Material Removal Rate and Surface Roughness are considered as outputs. In order to reduce the number of experiments Design of Experiments (DOE) was undertaken using Orthogonal Array and later on the outputs were optimized using ANN and PSO. It was found that the results obtained from both the techniques were tallying with each other.

Identification of Optimal Process Parameters in Electro-Discharge Machining Using ANN and PSO

2022 ◽  
pp. 824-842
Author(s):  
Kaushik Kumar ◽  
J. Paulo Davim
Keyword(s):  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Machining Process ◽  
Repair Work ◽  
Electro Discharge Machining ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Edm Process ◽  
Time Pulse

Electrical Discharge Machining (EDM) process is a widely used machining process in several fabrication, construction and repair work applications. Considering Pulse-On Time, Pulse OFF time, Peak-Current and Gap voltage as the inputs and among all possible outputs, in the present work Material Removal Rate and Surface Roughness are considered as outputs. In order to reduce the number of experiments Design of Experiments (DOE) was undertaken using Orthogonal Array and later on the outputs were optimized using ANN and PSO. It was found that the results obtained from both the techniques were tallying with each other.

scholarly journals Modeling and experimental investigation of process parameters in WEDM for surface roughness using regression model

2018 ◽  
Vol 172 ◽  
pp. 04010
Author(s):  
A. Muniappan ◽  
R. Senthilkumar ◽  
V. Jayakumar ◽  
S. Venkata Ravikumar ◽  
P. Sai Tarunkumar
Keyword(s):  
Surface Roughness ◽  
Multiple Regression ◽  
Process Parameters ◽  
Wire Tension ◽  
Level 3 ◽  
Level 1 ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Off Time

The present study focused on the multiple regression modeling and predicting the surface roughness of the Aluminum hybrid composite during the WEDM process. The hybrid MMC was manufactured by process named as stir casting utilizing particulates of Silicon carbide and graphite each in Al6061 combination. The analyses were outlined with Taguchi L27 design matrix. Mathematical relationships between the surface roughness and WEDM cutting parameters (Pulse on time, Pulse off time, current, gap voltage, wire speed and wire tension) have been investigated. The results show that the multiple regression analysis is a successful method for developing a mathematical model to predict the surface roughness. The optimum value of process parameters for the predicted optimum value of surface roughness (1.285) is pulse on time 106 units (Level 1), pulse off time 60 units (Level 3), peak current 90 units (Level 2), gap set voltage 50 units (Level 3), wire speed3 units (Level 1) and wire tension 12 units (Level 3).The optimum results are adopted in validation study and the results based on WEDM process responses can be effectively improved.

Performance Analysis on Eco-friendly Machining of Ti6Al4V using Powder Mixed with Different Dielectrics in WEDM

2020 ◽  
Vol 17 (3) ◽  
pp. 8128-8139
Author(s):  
S. Chakraborty ◽  
S. Mitra ◽  
D. Bose
Keyword(s):  
Metal Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Process Efficiency ◽  
Machining Parameters ◽  
Dielectric Fluids ◽  
High Emission ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

The recent scenario of modern manufacturing is tremendously improved in the sense of precision machining and abstaining from environmental pollution and hazard issues. In the present work, Ti6Al4V is machined through wire EDM (WEDM) process with powder mixed dielectric and analyzed the influence of input parameters and inherent hazard issues. WEDM has different parameters such as peak current, pulse on time, pulse off time, gap voltage, wire speed, wire tension and so on, as well as dielectrics with powder mixed. These are playing an essential role in WEDM performances to improve the process efficiency by developing the surface texture, microhardness, and metal removal rate. Even though the parameter’s influencing, the study of environmental effect in the WEDM process is very essential during the machining process due to the high emission of toxic vapour by the high discharge energy. In the present study, three different dielectric fluids were used, including deionised water, kerosene, and surfactant added deionised water and analysed the data by taking one factor at a time (OFAT) approach. From this study, it is established that dielectric types and powder significantly improve performances with proper set of machining parameters and find out the risk factor associated with the PMWEDM process.

Machining Characteristics Estimation in WEDM Process While Machining Titanium Grade-2 Material Using ANN

2020 ◽  
Author(s):  
Prathik Jain Sudhir ◽  
Ravindra Holalu Venkatadas ◽  
Ugrasen Gonchikar
Keyword(s):  
Process Parameters ◽  
Machining Process ◽  
Electrode Wear ◽  
Training Set ◽  
Hard Materials ◽  
Titanium Grade ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Machining Characteristics

Abstract Wire Electrical Discharge Machining (WEDM) provides an effective solution for machining hard materials with intricate shapes. WEDM is a specialized thermal machining process is capable to accurately machining parts of hard materials with complex shapes. However, selection of process parameters for obtaining higher machining efficiency or accuracy in wire EDM is still not fully solved, even with the most up-to-date CNC WED machine. The study presents the machining of Titanium grade 2 material using L’16 Orthogonal Array (OA). The process parameters considered for the present work are pulse on time, pulse off time, current, bed speed, voltage and flush rate. Among these process parameters voltage and flush rate were kept constant and the other four parameters were varied for the machining. Molybdenum wire of 0.18mm is used as the electrode material. Titanium is used in engine applications such as rotors, compressor blades, hydraulic system components and nacelles. Its application can also be found in critical jet engine rotating and airframes components in aircraft industries. Firstly optimization of the process parameters was done to know the effect of most influencing parameters on machining characteristics viz., Surface Roughness (SR) and Electrode Wear (EW). Then the simpler functional relationship plots were established between the parameters to know the possible information about the SR and EW. This simpler method of analysis does not provide the information on the status of the material and electrode. Hence more sophisticated method of analysis was used viz., Artificial Neural Network (ANN) for the estimation of the experimental values. SR and EW parameters prediction was carried out successfully for 50%, 60% and 70% of the training set for titanium material using ANN. Among the selected percentage data, at 70% training set showed remarkable similarities with the measured value then at 50% and 60%.

Influence of Process Parameters on Characteristics of Electrical Discharge Machining of PH17-4 Stainless Steel

2015 ◽  
Vol 14 (03) ◽  
pp. 189-202 ◽  
Author(s):  
V. Vikram Reddy ◽  
P. Madar Valli ◽  
A. Kumar ◽  
Ch. Sridhar Reddy
Keyword(s):  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Surface Hardness ◽  
Machining Process ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time

In the present work, an investigation has been made into the electrical discharge machining process during machining of precipitation hardening stainless steel PH17-4. Taguchi method is used to formulate the experimental layout, to analyze the effect of each process parameter on machining characteristics and to predict the optimal choice for each electrical discharge machining process parameters namely, peak current, pulse on time and pulse off time that give up optimal process performance characteristics such as material removal rate, surface roughness, tool wear rate and surface hardness. To identify the significance of parameters on measured response, the analysis of variance has been done. It is found that parameters peak current and pulse on time have the significant affect on material removal rate, surface roughness, tool wear rate and surface hardness. However, parameter pulse off time has significant affect on material removal rate. Confirmation tests are conducted at their respective optimum parametric settings to verify the predicted optimal values of performance characteristics.

Optimization of WEDM Process Parameters

2014 ◽  
Vol 592-594 ◽  
pp. 831-835 ◽  
Author(s):  
Vikram Singh ◽  
Sharad Kumar Pradhan
Keyword(s):  
Surface Roughness ◽  
Response Surface ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Parameters ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

The objective of the present work is to investigate the effects of various WEDM process parameters like pulse on time, pulse off time, corner servo, flushing pressure, wire feed rate, wire tension, spark gap voltage and servo feed on the material removal rate (MRR) & Surface Roughness (SR) and to obtain the optimal settings of machining parameters at which the material removal rate (MRR) is maximum and the Surface Roughness (SR) is minimum in a range. In the present investigation, Inconel 825 specimen is machined by using brass wire as electrode and the response surface methodology (RSM) is for modeling a second-order response surface to estimate the optimum machining condition to produce the best possible response within the experimental constraints.

Surface Roughness Optimization of Wire Electrical Discharge Machining Using ABC Algorithm

2015 ◽  
Vol 766-767 ◽  
pp. 902-907
Author(s):  
Bibin K. Tharian ◽  
B. Kuriachen ◽  
Josephkunju Paul ◽  
Paul V. Elson
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Wire Electrical Discharge Machining ◽  
Wire Tension ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Wire Feed

Wire electrical discharge machining is one of the important non-traditional machining processes for machining difficult to machine materials. It involves the removal of material by the discrete electric discharges produced between the inter electrode gap of continuously moving wire electrode and the work piece. The ability to produce intricate profiles on materials irrespective of the mechanical properties made this process to be widely used in industries. The present study investigates the relationship of various process parameters in WEDM of AISI 202 stainless steel with brass electrode.The experiments were planned according to Taguchi’s L18 orthogonal array and experimental models were developed. The important process parameters identified for the present study were pulse on time, peak current, pulse off time, wire feed, wire tension, dielectric flushing pressure, servo feed and gap voltage. The surface roughness of the machined surface was measured as the process performance measure. Analysis of variance test has also been carried out to check the adequacy of the developed models and to identify the level of significance of each process parameters. In addition to the developed models, ABC optimization has been performed to identify the optimum parameter combination for minimum surface roughness and the obtained optimal process parameters are peak current 11 A, pulse on time 100 μs, pulse off time 49 μs, wire feed 4 m/min, wire tension 10 N, flushing pressure 12 kg/cm2, servo feed 2100 mm/min and set gap voltage 30 V. Finally the results were verified with the experimental results and found that they are in good agreement.

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