scholarly journals Optimizing Process Parameters of Spark and Wire-Cut Edm through Anova using Stainless Steel Aisi 316 Material

2019 ◽  
Vol 9 (2) ◽  
pp. 817-821
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Process Parameters ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Parameters ◽  
Steel Aisi ◽  
Aisi 316 ◽  
Pulse On Time ◽  
Stainless Steel Aisi

In the present research work, Stainless Steel AISI 316 as per ASTM A 276 has been employed as the base material to perform Spark and Wire-Cut EDM. The main agenda behind performing Spark and Wire-Cut EDM on Stainless Steel AISI 316 is to find out the effect of machining parameters like surface roughness (SR) and MRR (Material Removal Rate). In-case of wire-cut EDM, brass wire) of 0.25 mm diameter is used as a tool and distilled water is used as dielectric fluid and experimental process parameters like Current (A) (2, 3 and 4 Amps), Pulse ON time (B) (25, 30 and 35 μs) and Wire feed rate (C) (40, 60 and 80 mm/sec). Similarly for spark cut EDM copper rod of 12 mm diameter and 65 mm length. Process parameters like Current (A) (6, 12 and 16 Amps), Voltage (B) (30, 35 and 40 Volts) and Pulse ON time (C) (50, 100 and 200μs) were maintained during the experimentation. Statistical tools ANOVA & L-9 Orthogonal Array (OA) have been employed to optimize the machining parameters like Surface Roughness (SR) and MRR (Material Removal Rate).

Multi Response Optimization of Process Parameters of Abrasive Water Jet Machining for Stainless Steel AISI 304 Using VIKOR Approach Coupled with Signal to Noise Ratio Methodology

2015 ◽  
Vol 14 (02) ◽  
pp. 107-121 ◽  
Author(s):  
Vedansh Chaturvedi ◽  
Diksha Singh
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Aisi 304 ◽  
Steel Aisi ◽  
Machining Characteristics ◽  
Stainless Steel Aisi ◽  
Experimental Runs

As the population of the world is continuously increasing, demand of the mechanical manufactured products is also increasing. Machining is the most important process in any mechanical manufacturing, and in machining two factors, i.e. material removal rate (MRR) and surface roughness (SR) are the most important responses. If the MRR is high, the product will get desired shape in minimum time so the production rate will be high, but we could not scarify with the surface finishing also because in close tolerance limit parts like in automobile industry, if the surface is rough exact fit cannot take place. The term optimization is intensively related to the field of quality engineering. Abrasive water jet machining is an important unconventional machining, in order to obtain better response, i.e. material removal rate and surface roughness. Various process parameters of AWJM need to be observed and selected to improve machining characteristics. Better machining characteristics can be achieved by optimizing various process parameters of AWJM. This study considers four process control parameters such as transverse speed, standoff distance, abrasive flow rate and water pressure. The response is taken to be material removal rate and surface roughness. The work piece for stainless steel AISI 304 material of size 15 cm × 10 cm × 2 cm is selected for experiments. Sixteen experimental runs (two trials for each experimental runs) were carried out for calculating MRR and SR and average value of these two trials have been taken for analysis. MRR is normalized according to higher-is-better and SR is normalized according to lower is better. The experiment data analysis is done and VIKOR index is found. Finally, the analysis of VIKOR index using S/N ratio is done and found the most significant factor for AWJM and predicted optimal parameters setting for higher material removal rate and lower surface roughness. Verification of the improvement in quality characteristics has been made through confirmation test with the predicted optimal parameters setting. It is found that the determined optimum combination of AWJM parameters gives the lowest VIKOR INDEX which shows the successful implementation of VIKOR Method coupled with S/N ratio in AWJM.

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 A Study on Optimization of Process Parameters in Machining of Bronze using Wire-EDM

2021 ◽  
pp. 484-493
Author(s):  
Gajanan Kamble ◽  
Dr. N. Lakshamanaswamy ◽  
Gangadhara H S ◽  
Sharon Markus ◽  
N. Rajath
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Machining Parameters ◽  
Wire Edm ◽  
Pulse On Time ◽  
Pulse Off Time

Wire cut electrical discharge machining (WEDM) is a hybrid manufacturing technology which enables machining of all engineering materials. This research article deals with investigation on Optimization of the Process Parameters of the wire cut EDM of Bronze material of dimension (80*80*40) in mm. Material removal rate, Surface roughness and Kerf width were studied against the process parameters such as Pulse on time(TON), Pulse off time (TOFF) and Current(IP). The machining parameters for wire EDM were optimized for achieving the combined objectives. As there are three input parameters 27 experiments is carried out and full factorial is used. Optimized parameters were found using (ANOVA) and the error percentage can be validated and parameter contribution for the Material removal rate (MRR) and Surface roughness were found.

Prediction of machining performance using RSM and ANN models in hard turning of martensitic stainless steel AISI 420

2019 ◽  
Vol 233 (13) ◽  
pp. 4439-4462 ◽  
Author(s):  
Abderrahmen Zerti ◽  
Mohamed Athmane Yallese ◽  
Oussama Zerti ◽  
Mourad Nouioua ◽  
Riad Khettabi
Keyword(s):  
Neural Network ◽  
Surface Roughness ◽  
Artificial Neural Network ◽  
Stainless Steel ◽  
Response Surface Methodology ◽  
Martensitic Stainless Steel ◽  
Machining Parameters ◽  
Steel Aisi ◽  
Artificial Neural ◽  
Stainless Steel Aisi

The purpose of this experimental work is to study the impact of the machining parameters ( Vc, ap, and f) on the surface roughness criteria ( Ra, Rz, and Rt) as well as on the cutting force components ( Fx, Fy, and Fz), during dry turning of martensitic stainless steel (AISI 420) treated at 59 hardness Rockwell cone. The machining tests were carried out using the coated mixed ceramic cutting-insert (CC6050) according to the Taguchi design (L25). Analysis of the variance (ANOVA) as well as Pareto graphs made it possible to quantify the contributions of ( Vc, ap, and f) on the output parameters. The response surface methodology and the artificial neural networks approach were used for output modeling. Finally, the optimization of the machining parameters was performed using desirability function (DF) minimizing the surface roughness and the cutting forces simultaneously. The results indicated that the roughness is strongly affected by the feed rate ( f) with contributions of (80.71%, 80.26%, and 81.80%) for ( Ra, Rz, and Rt) respectively, and that the depth of cut ( ap) is the factor having the major influence on the cutting forces ( Fx = 53.76%, Fy = 50.79%, and Fz = 65.31%). Furthermore, artificial neural network and response surface methodology models correlate very well with experimental data. However, artificial neural network models show better accuracy. The optimum machining setting for multi-objective optimization is Vc = 80 m/min, f = 0.08 mm/rev and ap = 0.141 mm.

Optimization of Process Parameters on Ti-6Al-4V Using Central Composite Design Method

2011 ◽  
Vol 189-193 ◽  
pp. 1393-1400 ◽  
Author(s):  
M.M. Rahman
Keyword(s):  
Surface Roughness ◽  
Wear Rate ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Peak Current ◽  
Long Pulse ◽  
Pulse On Time

Electrical discharge machining (EDM) is relatively modern machining process having distinct advantages over other machining processes and able to machine Ti-alloys effectively. This paper attempts to investigate the effects of process parameters on output response of titanium alloy Ti-6Al-4V in EDM utilizing copper tungsten as an electrode and positive polarity of the electrode. Mathematical models for material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR) are developed in this paper. Design of experiments method and response surface methodology techniques are implemented. The validity test of the fit and adequacy of the proposed models has been carried out through analysis of variance. It can be seen that as the peak current increases the TWR decreases till certain ampere and then increases. The excellent surface finish is investigated in this study at short pulse on time and in contrast the long pulse duration causes the lowest EWR. Long pulse off time provides minimum EWR and the impact of pulse interval on EWR depends on peak current. The result leads to wear rate of electrode and economical industrial machining by optimizing the input parameters. It found that the peak current, servo voltage and pulse on time are significant in material removal rate and surface roughness. Peak current has the greater impact on surface roughness and material removal rate.

scholarly journals Tool Wear Rate Prediction by using Optimization Techniques

2019 ◽  
Vol 9 (2) ◽  
pp. 1271-1277
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Optimization Techniques ◽  
Machining Process ◽  
Machining Parameters ◽  
Tungsten Carbides ◽  
Electro Discharge Machining ◽  
Pulse On Time

Electro discharge machining is a non-traditional machining process used for machining hard-to-machine materials, such as various grades of titanium alloys, heat-treated alloy steels, composites, tungsten carbides, and so forth. These materials are hard to machine with customary machining procedures like drilling, milling and hence electro-discharge machining is used to machine such materials to get better quality and efficiency. These materials are generally utilized in current industries like die making industries, aeronautics, nuclear industries, and medical fields. This type of machining is thermalbased, and machining takes place due to repetitive electric sparks that generate between workpiece and tool. Both tools and workpieces are inundated in a dielectric liquid, which has two primary functions. In the first place, it behaves like a medium between the work metal and the tool. Second, it is a flushing agent to expel the machined metal from the machined zone. Machining parameters like a pulse on time, current, wire feed the tool and gap voltage affect the output responses like surface roughness and material removal rate. The material removal rate is a significant parameter that determines machining efficiency. Surface roughness is also a vital parameter that decides machining quality. A lot of research has been conducted to determine the optimum parameters for obtaining the best results. In the present work, a comprehensive review of different types of EDM and the effect of various machining parameters on the surface roughness, material removal rate, and other response parameters has been done.

Effects of Process Parameters on Material Removal Rate and Surface Roughness in Wedm of H-13 Die Tool Steel

2018 ◽  
Vol 28 ◽  
pp. 55-66 ◽  
Author(s):  
Kuldeep Singh ◽  
Khushdeep Goyal ◽  
Deepak Kumar Goyal
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Tool Steel ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Pulse On Time ◽  
Pulse Off Time

In research work variation of cutting performance with pulse on time, pulse off time, wire type, and peak current were experimentally investigated in wire electric discharge machining (WEDM) process. Soft brass wire and zinc coated diffused wire with 0.25 mm diameter and Die tool steel H-13 with 155 mm× 70 mm×14 mm dimensions were used as tool and work materials in the experiments. Surface roughness and material removal rate (MRR) were considered as performance output in this study. Taguchi method was used for designing the experiments and optimal combination of WEDM parameters for proper machining of Die tool steel (H-13) to achieve better surface finish and material removal rate. In addition the most significant cutting parameter is determined by using analysis of variance (ANOVA). Keywords Machining, Process Parameters, Material removal rate, Surface roughness, Taguchi method

Statistical analysis of material removal rate and surface roughness in electrical discharge turning of titanium alloy (Ti-6Al-4V)

2016 ◽  
Vol 232 (9) ◽  
pp. 1603-1614 ◽  
Author(s):  
Vikas Gohil ◽  
Yogesh M Puri
Keyword(s):  
Surface Roughness ◽  
Titanium Alloy ◽  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Machining Parameters ◽  
Peak Current ◽  
Pulse On Time

Electrical discharge turning is a unique form of electrical discharge machining process, which is being especially developed to generate cylindrical forms and helical profiles on the difficult-to-machine materials at both macro and micro levels. A precise submerged rotating spindle as a work holding system was designed and added to a conventional electrical discharge machine to rotate the workpiece. A conductive preshaped strip of copper as a forming tool is fed (reciprocate) continuously against the rotating workpiece; thus, mirror image of the tool is formed on the circumference of the workpiece. The machining performance of electrical discharge turning process is defined and influenced by its machining parameters, which directly affects the quality of the machined component. This study presents an investigation on the effects of the machining parameters, namely, pulse-on time, peak current, gap voltage, spindle speed and flushing pressure, on the material removal rate (MRR) and surface roughness (Ra) in electrical discharge turning of titanium alloy Ti-6Al-4V. This has been done by means of Taguchi’s design of experiment technique. Analysis of variance as well as regression analysis is performed on the experimental data. The signal-to-noise ratio analysis is employed to find the optimal condition. The experimental results indicate that peak current, gap voltage and pulse-on time are the most significant influencing parameters that contribute more than 90% to material removal rate. In the context of Ra, peak current and pulse-on time come up with more than 82% of contribution. Finally, the obtained predicted optimal results were verified experimentally. It was shown that the error values are all less than 6%, confirming the feasibility and effectiveness of the adopted approach.

scholarly journals Experimental Investigation of Edm Die Sinking Process Parameters on Aluminium Alloy 5083 Using Design of Experiment

2017 ◽  
Vol 4 (1) ◽  
pp. 138-144
Author(s):  
Wahaizad Safiei ◽  
Muhamad Ridzuan Radin Muhamad Amin
Keyword(s):  
Surface Roughness ◽  
Aluminium Alloy ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Design Of Experiment ◽  
Material Removal ◽  
Removal Rate ◽  
Peak Current ◽  
Pulse On Time ◽  
Pulse Off Time

In this paper, the results of surface roughness (Ra) and material removal rate (MRR) are presented based on experimental studies of Electrical Discharge Machining (EDM) process parameters. Pulse ON time, pulse OFF time, peak current, gap voltage and jump speed are the selected input parameters and the experiments were conducted with Aluminium Alloy 5083 as a workpiece, copper as an electrode and the response variables are surface roughness (Ra) and material removal rate (MRR). Design of Experiment and Analysis of Variance (ANOVA) were applied to identify the optimum settings.The result shows that the significant factors for the value of surface roughness (Ra) and material removal rate (MRR) are pulses ON time and peak current.

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