Geometrical deviation identification and prediction method for additive manufacturing
Geometrical deviation identification and prediction method for additive manufacturing
复制标题
增材制造几何偏差识别与预测方法
DOI：
10.1108/rpj-07-2017-0137
复制
发表时间：
2018
影响因子：
3.9
通讯作者：
Nicolas Bonnet
中科院分区：
文献类型：
--
作者：
Zhicheng Huang;J. Dantan;A. Etienne;M. Rivette;Nicolas Bonnet
目的
如今阻碍增材制造 (AM) 进一步应用和获益的一个主要问题是，增材制造零件最终总是具有较差的几何质量。为了帮助提高增材制造的几何质量，本研究旨在提出增材制造几何偏差识别和预测方法，用于识别增材制造零件几何偏差的因素、形式和数值。
设计/方法论/途径
本文应用基于表皮模型的模态分解方法来描述增材制造的几何偏差，并将其分解为不同的缺陷模式。在此基础上，开发了提出和扩展缺陷模式的方法。然后用该方法进行几何偏差的识别和预测。最后，介绍了通过熔融沉积建模制造气缸的案例研究。使用两台具有不同测量方法的坐标测量机（CMM）来验证所提出的方法和模式的有效性。
研究结果
两台不同三坐标测量机的案例研究结果非常接近，这表明本文提出的方法和模式是非常有效的。此外，结果表明，主要的几何缺陷是由收缩和机器精度引起的误差引起的，而这些误差尚未得到充分研究。
原创性/价值
该工作可用于识别和预测增材制造几何偏差的形式和数值，有助于更有针对性地实现设计阶段增材制造零件几何质量的提高。
Purpose
One major problem preventing further application and benefits from additive manufacturing (AM) nowadays is that AM build parts always end up with poor geometrical quality. To help improving geometrical quality for AM, this study aims to propose geometrical deviation identification and prediction method for AM, which could be used for identifying the factors, forms and values of geometrical deviation of AM parts.
Design/methodology/approach
This paper applied the skin model-based modal decomposition approach to describe the geometrical deviations of AM and decompose them into different defect modes. On that basis, the approach to propose and extend defect modes was developed. Identification and prediction of the geometrical deviations were then carried out with this method. Finally, a case study with cylinders manufactured by fused deposition modeling was introduced. Two coordinate measuring machine (CMM) machines with different measure methods were used to verify the effectiveness of the methods and modes proposed.
Findings
The case study results with two different CMM machines are very close, which shows that the method and modes proposed by this paper are very effective. Also, the results indicate that the main geometrical defects are caused by the shrinkage and machine inaccuracy-induced errors which have not been studied enough.
Originality/value
This work could be used for identifying and predicting the forms and values of AM geometrical deviation, which could help realize the improvement of AM part geometrical quality in design phase more purposefully.