Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.matdes.2020.108840
Title: Dry mechanical-electrochemical polishing of selective laser melted 316L stainless steel
Authors: Bai, Y 
Zhao, C 
Yang, J 
Fuh, JYH 
Lu, WF 
Weng, C
Wang, H 
Issue Date: 1-Aug-2020
Publisher: Elsevier BV
Citation: Bai, Y, Zhao, C, Yang, J, Fuh, JYH, Lu, WF, Weng, C, Wang, H (2020-08-01). Dry mechanical-electrochemical polishing of selective laser melted 316L stainless steel. Materials and Design 193 : 108840-108840. ScholarBank@NUS Repository. https://doi.org/10.1016/j.matdes.2020.108840
Abstract: © 2020 The Authors This paper aims to improve the surface quality of 316L stainless steel parts manufactured by selective laser melting (SLM) using dry mechanical-electrochemical polishing (DMECP). DMECP is an advanced surface finishing method combining the advantages of both mechanical and electrochemical polishing techniques in a more environmentally friendly manner. In this paper, the SLM process-related defects causing poor surface quality are analysed first. The material removal mechanism of DMECP is investigated to continuously remove the oxide layers formed during polishing. Surface morphology and roughness evolution under different polishing conditions are characterised. The top surface roughness can be reduced by over 91% from 8.72 μm to 0.75 μm compared to side surface by over 93% from 12.10 to 0.80 μm. The material removal on the top surface is more efficient than that on the side surface under the same polishing condition. The secondary defects formed during polishing can be removed using mechanical polishing mode. The chemical element composition of the polished surface exhibits almost identical content to the initial 316L powders. Compared with the initial dark and rough surfaces, the results validate the capability of DMECP as an effective tool to improve the SLM surface quality and achieve a mirror finish.
Source Title: Materials and Design
URI: https://scholarbank.nus.edu.sg/handle/10635/172435
ISSN: 02641275
18734197
DOI: 10.1016/j.matdes.2020.108840
Appears in Collections:Staff Publications
Elements

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
1-s2.0-S0264127520303749-main.pdfPublished version10.68 MBAdobe PDF

OPEN

PublishedView/Download

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.