<strong>Effect of material and machining features in electric discharge machining of 6061Al/rock dust composites</strong>
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Title Statement |
<strong>Effect of material and machining features in electric discharge machining of 6061Al/rock dust composites</strong> |
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Added Entry - Uncontrolled Name |
Prakash, Kumarasamy Soorya; Mechanical Engineering, Anna University Regional Campus, Coimbatore 641 046, India Gopal, Pudhupalayam Muthukutti; Mechanical Engineering, Karpagam Academy of Higher Education, Coimbatore 641 021, India Rahul, Raghavan Nair; Mechanical Engineering, Musaliar College of Engineering and Technology, Kerala 689 653, India |
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Uncontrolled Index Term |
EDM, Silica, Rock dust, Taguchi, GRA, Optimisation |
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Summary, etc. |
The current research investigates the effect of electric discharge machining (EDM) and material parameters on material removal rate (MRR), tool wear rate (TWR) and surface roughness (Ra) while machining the novel aluminium rock dust composite. Experiments have been performed in Vidyunt EM 150 EDM machine by considering parameters namely discharge current, pulse ON time, pulse OFF time, reinforcement size and level. The composites have been prepared through stir casting method by reinforcing various sizes (10, 20 & 30 μm) of rock dust particles with aluminium 6061 and at different levels (5, 10 & 15%). Since the number of input parameter is more, Taguchi’s design of experiments has been used to reduce the number of trials and grey relational analysis (GRA) technique has been used for optimization. Analysis of variance has been performed to identify the significance of the parameters and it has been found that all the considered parameters have significant effect on response variables. But in the case of multi performance characteristics analysis, only pulse ON time and pulse OFF time have the significance over GRG. Pulse ON time has the highest influence (55.36 %) on the GRG followed by pulse OFF time with 17.6% and rock dust weight % with 7.8%. From the confirmation experiments, it could be well said that the developed regression equations predicts the response parameters with minimal error and the grey relational grade has been improved significantly. |
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Publication, Distribution, Etc. |
Indian Journal of Engineering and Materials Sciences (IJEMS) 2020-08-06 16:02:52 |
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Electronic Location and Access |
application/pdf http://op.niscair.res.in/index.php/IJEMS/article/view/45981 |
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Data Source Entry |
Indian Journal of Engineering and Materials Sciences (IJEMS); ##issue.vol## 27, ##issue.no## 2 (2020): IJEMS- April 2020 |
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Language Note |
en |
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Terms Governing Use and Reproduction Note |
Except where otherwise noted, the Articles on this site are licensed under Creative Commons License: CC Attribution-Noncommercial-No Derivative Works 2.5 India © 2015. The Council of Scientific & Industrial Research, New Delhi. |
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