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Author Alrbaey, K. ♦ Wimpenny, D. I. ♦ Al Barzinjy, A. A. ♦ Moroz, A.
Source SpringerLink
Content type Text
Publisher Springer US
File Format PDF
Copyright Year ©2016
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations
Subject Keyword additive manufacturing ♦ powder metallurgy ♦ stainless ♦ steel ♦ Characterization and Evaluation of Materials ♦ Tribology, Corrosion and Coatings ♦ Quality Control, Reliability, Safety and Risk ♦ Engineering Design
Abstract This three-level three-factor full factorial study describes the effects of electropolishing using deep eutectic solvents on the surface roughness of re-melted 316L stainless steel samples produced by the selective laser melting (SLM) powder bed fusion additive manufacturing method. An improvement in the surface finish of re-melted stainless steel 316L parts was achieved by optimizing the processing parameters for a relatively environmentally friendly (‘green’) electropolishing process using a Choline Chloride ionic electrolyte. The results show that further improvement of the response value-average surface roughness (Ra) can be obtained by electropolishing after re-melting to yield a 75% improvement compared to the as-built Ra. The best Ra value was less than 0.5 μm, obtained with a potential of 4 V, maintained for 30 min at 40 °C. Electropolishing has been shown to be effective at removing the residual oxide film formed during the re-melting process. The material dissolution during the process is not homogenous and is directed preferentially toward the iron and nickel, leaving the surface rich in chromium with potentially enhanced properties. The re-melted and polished surface of the samples gave an approximately 20% improvement in fatigue life at low stresses (approximately 570 MPa). The results of the study demonstrate that a combination of re-melting and electropolishing provides a flexible method for surface texture improvement which is capable of delivering a significant improvement in surface finish while holding the dimensional accuracy of parts within an acceptable range.
ISSN 10599495
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2016-05-27
Publisher Place New York
e-ISSN 15441024
Journal Journal of Materials Engineering and Performance
Volume Number 25
Issue Number 7
Page Count 11
Starting Page 2836
Ending Page 2846

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Source: SpringerLink