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熔融沉积制造表面粗糙度参数显著性及预测模型研究

  

  1. (华北电力大学机械工程系，河北 保定 071003)
  • 出版日期:2020-08-31 发布日期:2020-08-22
  • 基金资助:
    国家自然科学基金项目(51301068)；河北省高等学校科学技术研究项目(Z2015127)；河北省高等教育教学改革研究与实践项目(2018GJJG416)

Investigation of parameters significance and predicted model on surface roughness on fused deposition modeling

  1. (Department of Mechanical Engineering, North China Electric Power University, Baoding Hebei 071003, China)
  • Online:2020-08-31 Published:2020-08-22
  • Supported by:
    National Science Foundation of China (51301068); Science and Technology Research Project of Colleges and Universities in Hebei
    Province (Z2015127); Research and Practice Project of Higher Education Teaching Reform in Hebei Province (2018GJJG416)

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摘要： 为了确定影响熔融沉积制造(FDM)打印件表面粗糙度的显著性因素，设计了基于
温度、打印速度和层厚的9 组正交实验。通过探针式粗糙度仪测量打印件表面粗糙度，并进行
了信噪比计算和波动分析，确定了影响表面粗糙度的显著性因素。利用田口法、多元回归方程
和指数方程对表面粗糙度进行预测，确定FDM 打印件最小表面粗糙度的参数组合。分析结果
表明：层厚对于表面粗糙度的影响程度最大，温度次之，打印速度最小；为了验证其有效性和
适用性，针对不同打印模型和FDM 打印机进行了验证性实验。实验结果表明：在预测模型方
面，多元回归方程的预测结果优于指数方程和田口法。并且，上述结论对不同打印模型和FDM
打印机具有较为宽泛的适用性。

关键词: 熔融沉积制造工艺, 表面粗糙度, 显著性分析, 预测模型

Abstract: Nine orthogonal experiments consisting of temperature, printing speed, layer thickness
were designed to investigate the factors and rules influencing fused deposition modeling (FDM)
precision. Surface roughness was measured using portable surface roughness apparatus. The
significant factor influencing surface roughness was determined by calculating the signal-to-noise
ratio and conducting the variance analysis. By means of the Taguchi method, the multiple regression
equation and exponential equation were employed to predict the surface roughness and to determine
the parameter combination of minimum surface roughness of FDM printouts. Results of the analysis
reveal the following factors in order of the extent of their influence on surface roughness: layer
thickness > temperature > printing speed. Validation experiments were undertaken regarding different
printing models and FDM printers to verify the validity and adaptability of the analysis results.
Experiment results show that the prediction result of the multiple regression equation outperformed
that of the exponential equation and Taguchi method. Furthermore, the above conclusions exhibit
broad adaptability to different printing models and FDM printers.

Key words: fused deposition modeling technology, surface roughness, significance analysis, prediction model