Characterization of shape and dimensional accuracy of incrementally formed titanium sheet parts with intermediate curvatures between two feature types
Characterization of shape and dimensional accuracy of incrementally formed titanium sheet parts with intermediate curvatures between two feature types
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DOI：
10.1007/s00170-015-7649-2
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发表时间：
2016-03-01
影响因子：
3.4
通讯作者：
Ou, Hengan
中科院分区：
文献类型：
--
作者：
Behera, Amar Kumar;Lu, Bin;Ou, Hengan
单点渐进成形（SPIF）是一种相对较新的制造工艺，最近已用于形成植入器械的医用级钛板。然而，SPIF工艺的一个局限性可能是与原始设计的零件模型相比，最终零件的尺寸不准确。消除这些不准确性对于形成医疗植入物以满足所需公差是至关重要的。以前的准确性表征的工作表明，功能的行为是很重要的预测精度。在这项研究中，一组基本的几何形状组成的规则和自由形式的功能，形成使用SPIF来表征1级钛板零件的尺寸不准确性。然后生成使用多变量自适应回归样条（MARS）的响应表面函数，以将部件的STL模型的各个顶点处的偏差建模为几何形状参数（例如曲率、深度、到特征边界的距离、壁角、所生成的响应函数还用于预测特定临床植入物情况下的尺寸偏差，其中部件中的曲率位于在规则特征和自由形式特征之间。结果表明，一个混合的MARS响应面模型，使用加权平均的规则和自由曲面模型可以用于这种情况下，以提高平均预测精度在+/- 0.5 mm。预测的偏差显示出合理的匹配与实际形成的形状为植入物的情况下，并用于生成优化的刀具路径，最大限度地减少形状和尺寸的不准确性。此外，然后使用精度表征函数制造植入物部件以提高精度。结果表明，增量成形钛医疗植入物的形状和尺寸精度的改善。
Single point incremental forming (SPIF) is a relatively new manufacturing process that has been recently used to form medical grade titanium sheets for implant devices. However, one limitation of the SPIF process may be characterized by dimensional inaccuracies of the final part as compared with the original designed part model. Elimination of these inaccuracies is critical to forming medical implants to meet required tolerances. Prior work on accuracy characterization has shown that feature behavior is important in predicting accuracy. In this study, a set of basic geometric shapes consisting of ruled and freeform features were formed using SPIF to characterize the dimensional inaccuracies of grade 1 titanium sheet parts. Response surface functions using multivariate adaptive regression splines (MARS) are then generated to model the deviations at individual vertices of the STL model of the part as a function of geometric shape parameters such as curvature, depth, distance to feature borders, wall angle, etc. The generated response functions are further used to predict dimensional deviations in a specific clinical implant case where the curvatures in the part lie between that of ruled features and freeform features. It is shown that a mixed-MARS response surface model using a weighted average of the ruled and freeform surface models can be used for such a case to improve the mean prediction accuracy within +/- 0.5 mm. The predicted deviations show a reasonable match with the actual formed shape for the implant case and are used to generate optimized tool paths for minimized shape and dimensional inaccuracy. Further, an implant part is then made using the accuracy characterization functions for improved accuracy. The results show an improvement in shape and dimensional accuracy of incrementally formed titanium medical implants.