Deng Yong, Mao Zhongfa, Yang Nan, Niu Xiaodong, Lu Xiangdong
Intelligent Manufacturing Key Laboratory of Ministry of Education, Shantou University, Shantou 515063, China.
Digital Technology Research and Application Center, Shantou Polytechnic, Shantou 515078, China.
Materials (Basel). 2020 Apr 1;13(7):1601. doi: 10.3390/ma13071601.
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.
尽管增材制造的概念已经提出了几十年，但选择性激光熔化（SLM）领域的发展势头终于开始显现。在SLM中，密度和表面粗糙度作为SLM加工零件的重要质量指标，取决于加工参数。然而，文献中很少有关于在SLM过程中对它们进行协同优化以同时获得高相对密度和低表面粗糙度的研究。在这项工作中，采用响应面法研究了不同加工参数（激光功率、扫描速度和扫描间距）对SLM制造的316L不锈钢零件密度和表面粗糙度的影响。建立了加工参数与制造质量之间的统计关系模型。提出了一种同时考虑密度和表面粗糙度的多目标协同优化策略。实验结果表明，加工参数对密度和表面粗糙度的主要影响相似。我们观察到激光功率和扫描速度对上述目标质量有显著影响，但扫描间距的影响相对较小。基于上述优化，通过具有优化加工参数的SLM可以获得具有优异表面粗糙度和相对密度的316L不锈钢零件。
