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Experimental Investigation on Centreless Electro Discharge Texturing of Thin Walled Inconel-600 Tubes

Experimental Investigation on Centreless Electro Discharge Texturing of Thin Walled Inconel-600 Tubes

M S. Shekhawat, Harlal Singh Mali, AP S. Rathore
Copyright: © 2020 |Volume: 10 |Issue: 3 |Pages: 28
ISSN: 2156-1680|EISSN: 2156-1672|EISBN13: 9781799807537|DOI: 10.4018/IJMMME.2020070103
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MLA

Shekhawat, M S., et al. "Experimental Investigation on Centreless Electro Discharge Texturing of Thin Walled Inconel-600 Tubes." IJMMME vol.10, no.3 2020: pp.34-61. http://doi.org/10.4018/IJMMME.2020070103

APA

Shekhawat, M. S., Mali, H. S., & Rathore, A. S. (2020). Experimental Investigation on Centreless Electro Discharge Texturing of Thin Walled Inconel-600 Tubes. International Journal of Manufacturing, Materials, and Mechanical Engineering (IJMMME), 10(3), 34-61. http://doi.org/10.4018/IJMMME.2020070103

Chicago

Shekhawat, M S., Harlal Singh Mali, and AP S. Rathore. "Experimental Investigation on Centreless Electro Discharge Texturing of Thin Walled Inconel-600 Tubes," International Journal of Manufacturing, Materials, and Mechanical Engineering (IJMMME) 10, no.3: 34-61. http://doi.org/10.4018/IJMMME.2020070103

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Abstract

Electro discharge texturing is a texture fabrication technique. Inconel 600 has poor machinability in conventional processes due to its poor thermal conductance, high temperature strength, and work hardening nature. In this work, a centreless electro discharge process is employed to produce texturing on the external surfaces of circular tubes by using graphite electrode. Centreless work support and drive attachment was developed and adopted on ENC-35 EDM to perform experiments. This article details the experimental findings of the influence of four process parameters: peak current, gap voltage, pulse on time, and electrode interaction area on material removal rate, tool wear rate and surface roughness. Response surface methods and ANOVA techniques were employed for data analysis while the RSM's desirability approach was used to solve the multi-response optimization. A confirmation run is conducted by adjusting the variables at optimal level within the selected range. Conclusions are drawn for optimum parametric settings.

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