王俊伟,贺定勇,吴旭,王国红.选区激光熔化成形NiTi合金工艺参数对表面粗糙度的影响规律[J].表面技术,2024,53(9):200-208.
WANG Junwei,HE Dingyong,WU Xu,WANG Guohong.Effect of Process Parameters on Surface Roughness of NiTi Alloys Produced by Selected Laser Melting[J].Surface Technology,2024,53(9):200-208
选区激光熔化成形NiTi合金工艺参数对表面粗糙度的影响规律
Effect of Process Parameters on Surface Roughness of NiTi Alloys Produced by Selected Laser Melting
投稿时间:2023-04-10  修订日期:2023-10-16
DOI:10.16490/j.cnki.issn.1001-3660.2024.09.019
中文关键词:  选区激光熔化  NiTi形状记忆合金  田口方法  表面粗糙度  工艺优化
英文关键词:selective laser melting  NiTi shape memory alloy  Taguchi method  surface roughness  process optimization
基金项目:
作者单位
王俊伟 北京工业大学 材料科学与工程学院,北京 100124 
贺定勇 北京工业大学 材料科学与工程学院,北京 100124 
吴旭 北京工业大学 材料科学与工程学院,北京 100124 
王国红 北京工业大学 材料科学与工程学院,北京 100124 
AuthorInstitution
WANG Junwei College of Materials Science and Engineering, Beijing University of Technology, Beijing 100124, China 
HE Dingyong College of Materials Science and Engineering, Beijing University of Technology, Beijing 100124, China 
WU Xu College of Materials Science and Engineering, Beijing University of Technology, Beijing 100124, China 
WANG Guohong College of Materials Science and Engineering, Beijing University of Technology, Beijing 100124, China 
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中文摘要:
      目的 针对选区激光熔化(SLM)制备NiTi形状记忆合金表面粗糙度难以满足实际应用要求,通过优化工艺参数(激光功率、扫描速度、扫描间距)以有效地降低表面粗糙度以及研究各工艺参数对表面粗糙度的影响规律。方法 采用L16正交阵列的田口模型设计选区激光熔化制备NiTi样品的工艺参数,通过对表面粗糙度信噪比值进行统计方法分析以及样品表面形貌的表征,研究不同工艺参数对表面粗糙度的影响程度以及影响机理,最终优化出制备低表面粗糙度的工艺参数组合。结果 在激光功率为20 W和30 W时,NiTi粉末不能够充分熔化造成熔道不连续,使得样品表面起伏增大,粗糙度值最大到7.8 μm;增大激光功率到40 W和50 W时,粉末充分熔化,样品表面形貌明显改善;在相同功率下,扫描速度从200 mm/s增加到500 mm/s时,样品的粗糙度值也随之增大。结论 工艺参数对表面粗糙度影响的重要性顺序依次为激光功率、扫描速度、扫描间距;最终优化出的工艺参数组合为激光功率50 W、扫描速度200 mm/s、扫描间距0.07 mm,并在该工艺参数下制备的样品表面粗糙度值为1.38 μm,与模型预测的值1.43 μm接近,相差仅为9.97%。
英文摘要:
      Since the surface quality of the NiTi parts prepared byselected laser melting (SLM) technology is generally difficult to meet the requirements of the application due to the high surface roughness, the work aims to investigate the effects of laser power, scanning speed and hatch space on the surface roughness of NiTi alloy samples during the process of SLM NiTi parts. The pre-alloy NiTi powders were atomized by the electrode induction melting gas atomization technique (ALD, Germany) under the protection by argon gas. NiTi powders were observed by scanning electron microscopy (SEM). The particle size distribution (PSD) was measured by laser scattering particle size analyzer (HORIBA LA-960S, Japan). For experimental design, the model was created based on the Taguchi design model of the L16 orthogonal array. The range of laser power, scanning speed and hatch spacing was 20-50 W, 200-500 mm/s and 0.05-0.08 μm. The scanning strategy of laser rotation 67° between two consecutive layers was applied to produce NiTi parts, with a fixed layer thickness of 30 μm. NiTi samples of 6 mm× 6 mm× 6 mm were produced by SLM technology (EOS M100, Germany). The surface roughness value and surface morphology were measured by laser confocal microscope (Olympus LEXT OSLS4100, Japan). The surface roughness signal-to-noise (S/N) ratio was calculated by the equation. The S/N ratio was a logarithmic function used as an objective function for optimization, which was conductive to data analysis and prediction of optimal results. Samples are successfully prepared by SLM technology. The results showed that, at the laser power of 20 W and 30 W, the sample surface had high fluctuation due to the powder, which could not melt sufficiently to the unstable melt track during the process of SLM NiTi parts, with a maximum surface roughness value of 7.8 μm. When the value of laser power reached 50 W, the sample with low surface roughness value was obtained which was attributed to the stable melt track, with a minimum surface roughness value of 1.3 μm. The sample surface roughness value increased with the increase of scanning speed, at the same laser power, which was attributed to the time of NiTi powder melting increasing at low scanning speed. The decreasing of hatch spacing could remelt the adjacent laser track to improve the surface morphology of NiTi parts. However, the surface roughness affected was not obvious when the laser track was not unstable. The rank order of the process parameters on the surface roughness is laser power, scanning speed, hatching spacing after statistical methods are used to analyze the surface roughness signal-to-noise ratio. According to the mathematical model, the optimal combination of process parameters is laser power of 50 W, scanning speed of 200 mm/s and hatch space of 0.07 mm. The surface roughness value (1.38 μm) of the sample prepared by the final optimized process parameters combination is close to the predicted value (1.43 μm) by fitting equation. The difference of the surface roughness value is only 9.97%. The model provides an accurate guide for experiments for the study of SLM NiTi parts.
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