王靖,曾寿金,魏青天,等.选区激光熔化Ti6Al4V梯度多孔结构工艺优化[J].精密成形工程,2023,15(9):17-27.
WANG Jing,ZENG Shou-jin,WEI Qing-tian,et al.Process Optimization of Selective Laser Melting for Ti6Al4V Gradient Porous Structure[J].Journal of Netshape Forming Engineering,2023,15(9):17-27. |
| 选区激光熔化Ti6Al4V梯度多孔结构工艺优化 |
| Process Optimization of Selective Laser Melting for Ti6Al4V Gradient Porous Structure |
| 投稿时间：2023-04-10 |
| DOI：10.3969/j.issn.1674-6457.2023.09.003 |
| 中文关键词: 选区激光熔化 梯度多孔结构 成形质量 工艺优化 响应面分析 |
| 英文关键词: laser selective melting gradient porous structure forming quality process optimization response surface analysis |
| 基金项目:福建省自然科学基金(2021J011052);福建省区域发展项目(2020H4003);福建省科技型中小企业技术创新资金项目(2022C0027) |
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| 中文摘要: |
| 目的 获得成形质量良好的医用梯度多孔金属种植体。方法 基于响应面法(RSM)建立选区激光熔化成形工艺参数(激光功率、扫描速度及扫描间距)与样件致密度、表面粗糙度及孔隙率差值的数学模型。利用获取的致密度、表面粗糙度和孔隙率差值对样件成形质量进行表征，通过响应面方差分析获取SLM不同成形工艺参数对样件致密度、表面粗糙度和孔隙率差值的影响，得到成形质量最佳的工艺参数。结果 样件成形质量最佳的SLM成形工艺参数如下:激光功率为240 W，扫描速度为1 400 mm/s，扫描间距为0.08 mm。优化后样件成形质量的预测值如下:致密度为97.97%，表面粗糙度均值为6.88 μm，孔隙率差值为2.97%。试验结果表明，预测值与试验值基本吻合，所建立的数学模型可以准确预测样件成形质量。结论 通过响应面法试验设计及方差回归分析，确定了Ti6Al4V梯度多孔金属种植体SLM成形的最佳工艺参数。 |
| 英文摘要: |
| The work aims to obtain high-quality medical gradient porous metal implants. A mathematical model was established based on response surface methodology (RSM) to determine the selected laser melting forming process parameters (laser power, scanning speed, and scanning spacing), as well as the density, surface roughness, and pore difference of the sample. The obtained density, surface roughness, and pore difference were used to characterize the forming quality of the sample. The effects of different forming process parameters of SLM on density, surface roughness, and porosity were analyzed by variance analysis and response surface methodology, and the optimal process parameters for the best forming quality were obtained. The optimal SLM forming process parameters for the best forming quality of sample were laser power 240 W, scanning speed 1 400 mm/s and scanning spacing 0.08 mm. The predicted values of forming quality after optimization of parameters were density of 97.97%, surface roughness of 6.88 μm and pore difference of 2.97%. According to the results, the predicted values were basically consistent with the experimental values. Through the experimental design based on response surface methodology and variance regression analysis, the optimal process parameters of SLM for Ti6Al4V gradient porous metal implant are determined. |
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