Cargando…
Collaborative Optimization of Density and Surface Roughness of 316L Stainless Steel in Selective Laser Melting
Although the concept of additive manufacturing has been proposed for several decades, momentum in the area of selective laser melting (SLM) is finally starting to build. In SLM, density and surface roughness, as the important quality indexes of SLMed parts, are dependent on the processing parameters...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7178480/ https://www.ncbi.nlm.nih.gov/pubmed/32244593 http://dx.doi.org/10.3390/ma13071601 |
_version_ | 1783525465111134208 |
---|---|
author | Deng, Yong Mao, Zhongfa Yang, Nan Niu, Xiaodong Lu, Xiangdong |
author_facet | Deng, Yong Mao, Zhongfa Yang, Nan Niu, Xiaodong Lu, Xiangdong |
author_sort | Deng, Yong |
collection | PubMed |
description | Although the concept of additive manufacturing has been proposed for several decades, momentum in the area of selective laser melting (SLM) is finally starting to build. In SLM, density and surface roughness, as the important quality indexes of SLMed parts, are dependent on the processing parameters. However, there are few studies on their collaborative optimization during SLM to obtain high relative density and low surface roughness simultaneously in the literature. In this work, the response surface method was adopted to study the influences of different processing parameters (laser power, scanning speed and hatch space) on density and surface roughness of 316L stainless steel parts fabricated by SLM. A statistical relationship model between processing parameters and manufacturing quality is established. A multi-objective collaborative optimization strategy considering both density and surface roughness is proposed. The experimental results show that the main effects of processing parameters on the density and surface roughness are similar. We observed that the laser power and scanning speed significantly affected the above objective quality, but the influence of the hatch spacing was comparatively low. Based on the above optimization, 316L stainless steel parts with excellent surface roughness and relative density can be obtained by SLM with optimized processing parameters. |
format | Online Article Text |
id | pubmed-7178480 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-71784802020-04-28 Collaborative Optimization of Density and Surface Roughness of 316L Stainless Steel in Selective Laser Melting Deng, Yong Mao, Zhongfa Yang, Nan Niu, Xiaodong Lu, Xiangdong Materials (Basel) Article Although the concept of additive manufacturing has been proposed for several decades, momentum in the area of selective laser melting (SLM) is finally starting to build. In SLM, density and surface roughness, as the important quality indexes of SLMed parts, are dependent on the processing parameters. However, there are few studies on their collaborative optimization during SLM to obtain high relative density and low surface roughness simultaneously in the literature. In this work, the response surface method was adopted to study the influences of different processing parameters (laser power, scanning speed and hatch space) on density and surface roughness of 316L stainless steel parts fabricated by SLM. A statistical relationship model between processing parameters and manufacturing quality is established. A multi-objective collaborative optimization strategy considering both density and surface roughness is proposed. The experimental results show that the main effects of processing parameters on the density and surface roughness are similar. We observed that the laser power and scanning speed significantly affected the above objective quality, but the influence of the hatch spacing was comparatively low. Based on the above optimization, 316L stainless steel parts with excellent surface roughness and relative density can be obtained by SLM with optimized processing parameters. MDPI 2020-04-01 /pmc/articles/PMC7178480/ /pubmed/32244593 http://dx.doi.org/10.3390/ma13071601 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Deng, Yong Mao, Zhongfa Yang, Nan Niu, Xiaodong Lu, Xiangdong Collaborative Optimization of Density and Surface Roughness of 316L Stainless Steel in Selective Laser Melting |
title | Collaborative Optimization of Density and Surface Roughness of 316L Stainless Steel in Selective Laser Melting |
title_full | Collaborative Optimization of Density and Surface Roughness of 316L Stainless Steel in Selective Laser Melting |
title_fullStr | Collaborative Optimization of Density and Surface Roughness of 316L Stainless Steel in Selective Laser Melting |
title_full_unstemmed | Collaborative Optimization of Density and Surface Roughness of 316L Stainless Steel in Selective Laser Melting |
title_short | Collaborative Optimization of Density and Surface Roughness of 316L Stainless Steel in Selective Laser Melting |
title_sort | collaborative optimization of density and surface roughness of 316l stainless steel in selective laser melting |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7178480/ https://www.ncbi.nlm.nih.gov/pubmed/32244593 http://dx.doi.org/10.3390/ma13071601 |
work_keys_str_mv | AT dengyong collaborativeoptimizationofdensityandsurfaceroughnessof316lstainlesssteelinselectivelasermelting AT maozhongfa collaborativeoptimizationofdensityandsurfaceroughnessof316lstainlesssteelinselectivelasermelting AT yangnan collaborativeoptimizationofdensityandsurfaceroughnessof316lstainlesssteelinselectivelasermelting AT niuxiaodong collaborativeoptimizationofdensityandsurfaceroughnessof316lstainlesssteelinselectivelasermelting AT luxiangdong collaborativeoptimizationofdensityandsurfaceroughnessof316lstainlesssteelinselectivelasermelting |