Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/332783
Title: Edm machining analysis of zirconium and nickel powder mixed dielectric on performance of high carbon high chromium steel
Researcher: Vijayakumar N
Guide(s): Ramesh S
Keywords: Engineering and Technology
Engineering
Engineering Mechanical
chromium steel
Edm machining
University: Anna University
Completed Date: 2020
Abstract: Electrical Discharge Machining (EDM) is a well-founded machining option in the development of the manufacturing industry. It is appropriate for extremely difficult for the processing, complex rigid material parts by conventional machining processes. By using EDM, various kinds of products can be manufactured like dies, molds, automobile components, parts of aircraft, spacecraft, and surgical components could be completely machined by EDM. Recently, the mechanical industry has achieved an exponential increase in its production capacity but still, EDM is not used at their complete efficiency. This limitation is a result of the failure to run the EDM optimally operating conditions.This research work is mainly concentrated on aspects related to metal removal rates, which are one of the most essential characteristics to select the optimal condition of the process and economic aspect. The effect of process variables like pulse off time, pulse on time and peak current, and on response parameters like Surface Roughness (SR) and Material Removal Rate (MRR), has been investigated by not mixing any powder, mixing zirconium and nickel powder independently and blended equal amount of zirconium and nickel powder into the dielectric fluid for PMEDM of HCHCr die steel utilizing copper is in the form of electrode. In the present study, the model for output response which is used to predict the material removal rate and surface roughness was developed by utilizing RSM. Further the statistical analysis of variance (ANOVA) was carried out to find out which process parameters are more important and the optimization of these multiple performances was derived by utilizing Grey relational analysis (GRA). newline
Pagination: xviii, 149p
URI: http://hdl.handle.net/10603/332783
Appears in Departments:Faculty of Mechanical Engineering

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10_listofabbreviations.pdf26.71 kBAdobe PDFView/Open
11_chapter1.pdf4.47 MBAdobe PDFView/Open
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13_chapter3.pdf4.53 MBAdobe PDFView/Open
14_chapter4.pdf4.53 MBAdobe PDFView/Open
15_chapter5.pdf4.53 MBAdobe PDFView/Open
16_chapter6.pdf4.52 MBAdobe PDFView/Open
17_conclusion.pdf4.52 MBAdobe PDFView/Open
18_references.pdf4.52 MBAdobe PDFView/Open
19_listofpublications.pdf4.47 MBAdobe PDFView/Open
80_recommendation.pdf65.94 kBAdobe PDFView/Open
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