In this research, the effects of Selective Laser Melting (SLM) process parameters comprising laser power, scan speed, hatch space and scan pattern angle on the formation of porosity and subsequently density have been analysed. To improve the mechanical properties, post-processes (heat treatment) must be performed. Therefore, heat treatment was added to the design of experiment to analyse the effect of this process coupling with SLM process parameters on the value of density. A comprehensive design set with five levels for each parameter was selected so Taguchi L25 was used as the design of experiment. The significance of each parameter on obtained results was examined using statistical analysis (F-Test) and numerical model (interrogator analysis). The correlation between two process parameters was discussed by using 3D analytical and contour plots and the mechanisms behind these were discussed in depth. The contribution of this paper is a deep investigation of the relation of process parameters and heat treatment on density based on the Artificial Neural Network model. Results showed that better density is obtained with lower scan speed, laser power and scanning pattern angle. Meanwhile, for heat treatment and hatch space, the best density was obtained in their optimum range.

在这项研究中，已经分析了包括激光功率，扫描速度，舱口空间和扫描图案角度在内的选择性激光熔融（SLM）工艺参数对孔隙形成以及随后的密度的影响。为了改善机械性能，必须执行后处理（热处理）。因此，在实验设计中增加了热处理，以分析该工艺与SLM工艺参数耦合对密度值的影响。选择了每个参数具有五个级别的综合设计集，因此Taguchi L25被用作实验设计。使用统计分析（F-Test）和数值模型（询问器分析）检查了每个参数对获得结果的重要性。通过使用3D分析图和轮廓图讨论了两个过程参数之间的相关性，并深入讨论了其背后的机理。本文的贡献是基于人工神经网络模型深入研究了工艺参数和热处理与密度之间的关系。结果表明，以较低的扫描速度，激光功率和扫描图案角度可获得更好的密度。同时，对于热处理和舱口空间，在其最佳范围内可获得最佳密度。激光功率和扫描图案角度。同时，对于热处理和舱口空间，在其最佳范围内可获得最佳密度。激光功率和扫描图案角度。同时，对于热处理和舱口空间，在其最佳范围内可获得最佳密度。