scholarly journals Experimental Investigations on The Effect of Tungsten Content on the Machining Behaviour of Tungsten Heavy Alloys

2021 ◽  
Vol 71 (2) ◽  
pp. 162-170
Author(s):  
Chithajalu Kiran Sagar ◽  
Amrita Priyadarshini ◽  
Amit Kumar Gupta

The present work attempts to assess the machinability of tungsten heavy alloys (WHAs) with varying tungsten content in terms of different machining characteristics such as chip thickness, material removal rate, cutting force and surface roughness under varied cutting conditions. The feed rate is found to have major influence on the machining characteristics; whereas the effect of rake angle appears to be marginal. With increase in W content both cutting force and material removal rate increase whereas surface roughness decreases. Since WHAs are difficult to machine, an additional objective of the study is to optimize machining parameters. An optimal balance of the experimental cutting parameters using Grey relational analysis has been achieved, which can be effectively employed for the machining of the alloys with close dimensional tolerances and desirable surface finish.

2015 ◽  
Vol 14 (02) ◽  
pp. 107-121 ◽  
Author(s):  
Vedansh Chaturvedi ◽  
Diksha Singh

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.


2014 ◽  
Vol 592-594 ◽  
pp. 831-835 ◽  
Author(s):  
Vikram Singh ◽  
Sharad Kumar Pradhan

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.


Author(s):  
Banwait S.S. ◽  
◽  
Sanjay S ◽  

The present work explains the machining of Titanium alloy using Electric Discharge Machining & Electro-Chemical Machining. This work aims to analyze the role of Current, Pulse on Time, Voltage and hence optimize the Material Removal Rate and Surface Roughness in Electric Discharge Machining. In the same way, it also aims to analyze the role of Concentration, Feed, and Voltage and optimize the Material Removal Rate and Surface Roughness in Electro-Chemical Machining. The various approaches like Taguchi & Analysis of Variance are executed to study the performance characteristics of the input parameters on the output parameters. The whole work is followed by a validation test and hence confirming the obtained values. Thus, it reveals the acceptability of the model. The work tells that Material Removal Rate and Surface Finish effect is more in Electro-Chemical Machining as compared to Electric Discharge Machining. For Material Removal Rate, Current and Feed are more responsible parameters for Electric Discharge Machining. In the same way; electrolyte concentration and Feed are more responsible parameters for Electro-Chemical Machining respectively.


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.


Author(s):  
Gaurav Pandey

Abstract: The proper selection of machining conditions and machining parameter is an important aspect, before going to machine a carbon-fiber composite material by Die sinking electrical discharge machining (EDM). Because these conditions will determine such important characteristics as; Material removal rate (MRR), Electrode wears rate (EWR), and Surface roughness (R). The purpose of this work is to determine the optimal values of machining parameters of electrical discharge machine, while machining carbon-fiber-composite with copper electrode. The work has been based on the affect of four design factors: pulse current(Ip) supplied by power supply system of electrical discharge machine (EDM), pulse-on-time(TON), gap voltage(Vg) and duty cycle () on such characteristic like material removal rate (MRR), electrode wear rate(EWR), and surface roughness(Ra) on work-piece surface. This work has been done by means of the technique of design of experiment (DOE), which provides us to perform the above-mentioned analysis with small number of experiments. In this work, a L9 orthogonal array is used to design the experiment. The adequate selection of machining parameters is very important in manufacturing system, because these parameters determine the surface quality and dimensional accuracy of the manufactured part. The optimal setting of the parameters are determined through experiments planned, conducted and analyzed using the Taguchi method. It is found that material removal rate (MRR) reduces substantially, within the region of experimentation, if the parameters are set at their lowest values, while the parameters set at their highest values increases electrode wear rate (EWR). Keywords: EDM, Material removal rate, Surface roughness, Tool wear rate,


Author(s):  
Vikas Gohil ◽  
Yogesh M Puri

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.


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