Offline Predictive Control of Out-of-Plane Shape Deformation for Additive Manufacturing

Yuan JIN, S. Joe QIN, Qiang HUANG

Research output: Journal PublicationsJournal Article (refereed)peer-review

34 Citations (Scopus)

Abstract

Additive manufacturing (AM) is a promising direct manufacturing technology, and the geometric accuracy of AM built products is crucial to fulfill the promise of AM. Prediction and control of three-dimensional (3D) shape deformation, particularly out-of-plane geometric errors of AM built products, have been a challenging task. Although finiteelement modeling has been extensively applied to predict 3D deformation and distortion, improving part accuracy based purely on such simulation still needs significant methodology development. We have been establishing an alternative strategy that can be predictive and transparent to specific AM processes based on a limited number of test cases. Successful results have been accomplished in our previous work to control in-plane (x-y plane) shape deformation through offline compensation. In this study, we aim to establish an offline out-of-plane shape deformation control approach based on limited trials of test shapes. We adopt a novel spatial deformation formulation in which both in-plane and out-of-plane geometric errors are placed under a consistent mathematical framework to enable 3D accuracy control. Under this new formulation of 3D shape deformation, we develop a prediction and offline compensation method to reduce out-of-plane geometric errors. Experimental validation is successfully conducted to validate the developed 3D shape accuracy control approach.
Original languageEnglish
Article number121005
JournalJournal of Manufacturing Science and Engineering, Transactions of the ASME
Volume138
Issue number12
Early online date25 Jul 2016
DOIs
Publication statusPublished - Dec 2016
Externally publishedYes

Bibliographical note

This work was supported by the U.S. National Science Foundation with Grant No. CMMI-1544917. We thank Professor Yong Chen and Mr. Kai Xu for AM experimental support.

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