Citation: Bian, P.; Wang, C.; Xu, K.;
Ye, F.; Zhang, Y.; Li, L. Coupling
Analysis on Microstructure and
Residual Stress in Selective Laser
Melting (SLM) with Varying Key
Process Parameters. Materials 2022,
15, 1658. https://doi.org/10.3390/
ma15051658
Academic Editors: Ludwig Cardon
and Clemens Holzer
Received: 9 January 2022
Accepted: 11 February 2022
Published: 23 February 2022
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Article
Coupling Analysis on Microstructure and Residual Stress in
Selective Laser Melting (SLM) with Varying Key
Process Parameters
Peiying Bian
1,
* , Chunchang Wang
2
, Kewei Xu
1
, Fangxia Ye
1
, Yongjian Zhang
1
and Lei Li
1
1
Xi’an Key Laboratory on Intelligent Additive Manufacturing Technologies, Shaanxi Key Laboratory of Surface
Engineering and Remanufacturing, Xi’an University, Xi’an 710065, China; bobal@163.com (K.X.);
yfx324@163.com (F.Y.); zhangyongjian@mail.nwpu.edu.cn (Y.Z.); lilei1634@sina.com (L.L.)
2
Shaanxi Tyon Intelligent Remanufacturing Co., Ltd., Xi’an 710018, China; susanzhaoyue@163.com
* Correspondence: banry3@163.com
Abstract:
With the application of Selective Laser Melting (SLM) technology becoming more and more
widespread, it is important to note the process parameters that have a very important effect on the
forming quality. Key process parameters such as laser power (P), scan speed (s), and scanning strategy
(
µ
) were investigated by determining the correlation between the microstructure and residual stress in
this paper. A total of 10 group 316L specimens were fabricated using SLM for comprehensive analysis.
The results show that the key process parameters directly affect the morphology and size of the molten
pool in the SLM deposition, and the big molten pool width has a direct effect on the larger grain size
and crystal orientation distribution. In addition, the larger grain size and misorientation angle also
affect the size of the residual stress. Therefore, better additive manufacturing grain crystallization
can be obtained by reasonably adjusting the process parameter combinations. The transfer energy
density can synthesize the influence of four key process parameters (P, v, the hatching distance (
δ
),
and the layer thickness (h)). In this study, it is proposed that the
accepted energy density
will reflect
the influence of five key process parameters, including the scanning trajectory (
µ
), which can reflect
the comprehensive effect of process parameters more accurately.
Keywords: selective laser melting (SLM); process parameters; microstructure; residual stress
1. Introduction
Additive manufacturing (AM) has a unique forming concept and several advantages;
therefore, selective laser melting (SLM) is increasingly being used in small batches of parts
that are difficult to machine [
1
]; however, because of the high requirements of SLM process
parameter matching, it is difficult to directly control these parameters for better product
performance [
2
]. In many production applications, the parameters need to be adjusted
several times in order to make the necessary printed parts and, in some cases, manufactur-
ing failure caused by inappropriate process sequences is also common. According to the
literature [
3
], there are more than 130 process parameters that affect product performance,
but there are five key parameters—laser power (P), scan speed (s), scanning strategy (
µ
),
hatching distance (
δ
), and layer thickness (h). According to recent research, the mismatch
of these process parameters forms an unbalanced temperature field, and the resulting large
temperature gradient generates high thermal stress, resulting in corresponding defects such
as air gaps [
4
], warpage [
5
], cracks [
6
], and geometric error [
7
], which lead to a decrease in
the mechanical properties or to the deposition failure of the formed parts. Recently, there
have been many reports on related process parameters and their corresponding mechanical
properties, such as tensile properties [
8
], fatigue [
9
], hardness [
10
], surface roughness [
11
],
and residual stress [
12
]. In our previous study [
13
], the influence of laser power and
scanning strategy on residual stress distribution in 316L steel had been confirmed with a
Materials 2022, 15, 1658. https://doi.org/10.3390/ma15051658 https://www.mdpi.com/journal/materials
