Modeling and Optimization of EDM of Al 7075/10wt% Al2O3 Metal Matrix Composites by Response Surface Method

2012 ◽  
Vol 488-489 ◽  
pp. 856-860 ◽  
Author(s):  
S. Gopalakannan ◽  
Thiyagarajan Senthilvelan ◽  
K. Kalaichelvan
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Process Parameters ◽  
Metal Matrix ◽  
Removal Rate ◽  
Electrode Wear ◽  
Influence Of Process Parameters ◽  
Surface Method ◽  
Pulse On Time ◽  
Pulse Off Time

The newly engineered metal matrix composite (MMC) of aluminium 7075 reinforced with 10 wt% of Al2O3 particles were prepared by stir casting method. Electrical discharge machining (EDM) was employed to machine MMC with copper electrode. The experiment plan adopts face centered central composite design of response surface methodology. Analysis of variance was applied to investigate the influence of process parameters and their interactions viz., pulse current, gap voltage, pulse on time and pulse off time on material removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR). The objective was to identify the significant process parameters that affect the output characteristics. Further a mathematical model has been formulated by applying response surface method in order to estimate the machining characteristics such as MRR, EWR and SR.

Optimization and surface modification in electrical discharge machining of AA 6061/SiCp composite using Cu–W electrode

2015 ◽  
Vol 231 (3) ◽  
pp. 332-348 ◽  
Author(s):  
Balbir Singh ◽  
Jatinder Kumar ◽  
Sudhir Kumar
Keyword(s):  
Process Parameters ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Surface Characteristics ◽  
Electrode Wear ◽  
Material Transfer ◽  
Machined Surface ◽  
Recast Layer Thickness ◽  
Pulse On Time ◽  
Pulse Off Time

This paper presents the experimental investigation on the electro-discharge machining of aluminum alloy 6061 reinforced with SiC particles using sintered Cu–W electrode. Experiments have been designed as per central composite rotatable design, using response surface methodology. Machining characteristics such as material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR) have been investigated under the influence of four electrical process parameters; namely peak current, pulse on time, pulse off time, and gap voltage. The process parameters have been optimized to obtain optimal combination of MRR, EWR, and SR. Further, the influence of sintered Cu–W electrode on surface characteristics has been analyzed with scanning electron microscopy, energy dispersive spectroscopy, and Vicker microhardness tests. The results revealed that all the process parameters significantly affect MRR, EWR, and SR. The machined surface properties are modified as a result of material transfer from the electrode. The recast layer thickness is increased at higher setting of electrical parameters. The hardness across the machined surface is also increased by the use of sintered Cu–W electrode.

Optimization of Machining Parameters on Surface Roughness in EDM of Ti-6Al-4V Using Response Surface Method

2011 ◽  
Vol 213 ◽  
pp. 402-408 ◽  
Author(s):  
M.M. Rahman ◽  
Md. Ashikur Rahman Khan ◽  
M.M. Noor ◽  
K. Kadirgama ◽  
Rosli A. Bakar
Keyword(s):  
Surface Roughness ◽  
Response Surface ◽  
Response Surface Method ◽  
Surface Finish ◽  
Machining Parameters ◽  
Surface Method ◽  
Superior Surface ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time

This paper presents the influence of EDM parameters in terms of peak ampere, pulse on time and pulse off time on surface roughness of titanium alloy (Ti-6Al-4V). A mathematical model for surface finish is developed using response surface method (RSM) and optimum machining setting in favor of surface finish are evaluated. Design of experiments (DOE) techniques is implemented. Analysis of variance (ANOVA) has been performed to verify the fit and adequacy of the developed mathematical models. The acquired results yield that the increasing pulse on time causes fine surface till a certain value and then deteriorates the surface finish. It is investigated that about 200 µs pulse off time produce superior surface finish. These results lead to desirable surface roughness and economical industrial machining by optimizing the input parameters.

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.

scholarly journals Optimizing Main Process Parameters When Conducting Powder-Mixed Electrical Discharge Machining of Hardened 90CrSi

Machines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 375
Author(s):  
Anh-Tuan Nguyen ◽  
Xuan-Hung Le ◽  
Van-Tung Nguyen ◽  
Dang-Phong Phan ◽  
Quoc-Hoang Tran ◽  
...  
Keyword(s):  
Process Parameters ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Optimization Process ◽  
Main Process ◽  
Electrode Wear ◽  
Powder Concentration ◽  
Pulse On Time ◽  
Pulse Off Time

In the current study, an optimization process of powder-mixed electrical discharge machining (PMEDM) process when machining cylindrically shaped parts made of hardened 90CrSi steel is reported. In this study, SiC powder was mixed into the Diel MS 7000 dielectric solution. Additionally, graphite was chosen as the electrode material. The multi-objective functions were minimizing the surface roughness (SR) and electrode wear rate (EWR) and maximizing the material removal rate (MRR). The used input parameters of the optimization process included the powder concentration, the pulse-on time, the pulse-off time, the pulse current, and the servo voltage. A combination between the Taguchi method and the grey relation analysis (GRA) method with the support of Minitab R19 software was used to design the experiment and analyze the results. It was found that the optimal set of process parameters that can satisfy the above responses are Cp of 0.5 g/L, Ton of 8 µs, Toff of 8 µs, IP of 5 A, and SV of 4 V.

scholarly journals Optimizing Laser Powder Bed Fusion Parameters for IN-738LC by Response Surface Method

Materials ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 4879
Author(s):  
Mireia Vilanova ◽  
Rubén Escribano-García ◽  
Teresa Guraya ◽  
Maria San Sebastian
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Process Parameters ◽  
Crack Density ◽  
Processing Parameters ◽  
Optimum Process ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Surface Method

A method to find the optimum process parameters for manufacturing nickel-based superalloy Inconel 738LC by laser powder bed fusion (LPBF) technology is presented. This material is known to form cracks during its processing by LPBF technology; thus, process parameters have to be optimized to get a high quality product. In this work, the objective of the optimization was to obtain samples with fewer pores and cracks. A design of experiments (DoE) technique was implemented to define the reduced set of samples. Each sample was manufactured by LPBF with a specific combination of laser power, laser scan speed, hatch distance and scan strategy parameters. Using the porosity and crack density results obtained from the DoE samples, quadratic models were fitted, which allowed identifying the optimal working point by applying the response surface method (RSM). Finally, five samples with the predicted optimal processing parameters were fabricated. The examination of these samples showed that it was possible to manufacture IN738LC samples free of cracks and with a porosity percentage below 0.1%. Therefore, it was demonstrated that RSM is suitable for obtaining optimum process parameters for IN738LC alloy manufacturing by LPBF technology.

scholarly journals Multi-Objective Optimization of Process Parameters for Powder Mixed Electrical Discharge Machining of Inconel X-750 Alloy Using Taguchi-Topsis Approach

2021 ◽  
Vol 71 (1) ◽  
pp. 1-18
Author(s):  
Basha Shaik Khadar ◽  
Raju M. V. Jagannadha ◽  
Kolli Murahari
Keyword(s):  
Boron Carbide ◽  
Process Parameters ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Optimization Technique ◽  
Dielectric Fluid ◽  
Carbide Powder ◽  
Powder Concentration ◽  
Pulse On Time ◽  
Pulse Off Time

Abstract The paper investigates the influence of boron carbide powder (B4C) mixed in dielectric fluid on EDM of Inconel X-750 alloy. The process parameters selected as discharge current (Ip), pulse on time(Ton), pulse off time(Toff), boron carbide(B4C) powder concentration to examine their performance responses on Material Removal Rate (MRR), Surface Roughness(Ra) and Recast Layer Thickness (RLT).In this study, o examine the process parameters which influence the EDM process during machining of Inconel X-750 alloy using combined techniques of Taguchi and similarity to ideal solutions (TOPSIS).Analysis of variance (ANOVA) was conducted on multi-optimization technique of Taguchi-TOPSIS. ANOVA results identified the best process parameters and their percentages. It developed the mathematical equation on Taguchi-TOPSIS performance characteristics results. The multi optimization results indicated that Ip and Toff are more significant parameters; V, and Ton parameters are less significant. Finally, surface structures were studied at optimized EDM conditions by using scanning electron microscope (SEM).

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%.

Optimization of a nanoparticle ball milling process parameters using the response surface method

2018 ◽  
Vol 29 (9) ◽  
pp. 2129-2139 ◽  
Author(s):  
Srdjan Petrović ◽  
Ljiljana Rožić ◽  
Vesna Jović ◽  
Stevan Stojadinović ◽  
Boško Grbić ◽  
...  
Keyword(s):  
Response Surface ◽  
Ball Milling ◽  
Response Surface Method ◽  
Process Parameters ◽  
Milling Process ◽  
Ball Milling Process ◽  
Surface Method
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