Geometric deviations arising from multiple variation sources in Additive Manufacturing (AM) process chain have been a major issue regarding product quality. Therefore, effective modeling of the geometric deviations is becoming critical for AM. In this paper, in-plane geometric deviations are investigated based on the assumption that typical deviation sources in AM can be mapped to different transformations (scaling, rotation, translation) on the nominal shape. By defining transformation parameters, analytical deviation models of regular shapes can be derived in the deviation space, and calibrated based on measurement data. A case study is presented to show the effectiveness of the proposed approach.
Zhu, Z., Anwer, N., & Mathieu, L. (2018). Shape transformation perspective for geometric deviation modeling in additive manufacturing. In Procedia CIRP (Vol. 75, pp. 75–80). Elsevier B.V. https://doi.org/10.1016/j.procir.2018.04.038