TY - GEN
T1 - Real-time control for large scale additive manufacturing using thermal images
AU - Wang, Feifan
AU - Ju, Feng
AU - Rowe, Kyle
AU - Hofmann, Nils
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Large scale additive manufacturing has process mechanisms similar to Fused Filament Fabrication (FFF) and can print parts with large sizes, such as car bodies. This capability provides large scale additive manufacturing great application potentials in a variety of industries, including aerospace, automotive manufacturing, and construction. To make large scale additive manufacturing a viable manufacturing solution, both production efficiency and product quality need to be considered. Specifically, the printing process is subject to constraints on print surface temperature to guarantee good product quality. In this paper, we propose a novel method for controlling layer time during the printing process by using thermal images. Specifically, several thin wall test components are printed by the Thermwood Large Scale Additive Manufacturing (LSAM™) machine, and the print surface temperature is monitored by a FLIR™ thermal camera. A regression model based on real-time thermal imaging data is built to predict the surface temperature. Then a layer time control method is proposed based on the temperature prediction model. By comparing the proposed method to the fixed layer time policy, the experiment results suggest that the control method by using real-time data can siginificantly reduce the layer time, and subsequently the total printing time, while satisfying the quality requirement.
AB - Large scale additive manufacturing has process mechanisms similar to Fused Filament Fabrication (FFF) and can print parts with large sizes, such as car bodies. This capability provides large scale additive manufacturing great application potentials in a variety of industries, including aerospace, automotive manufacturing, and construction. To make large scale additive manufacturing a viable manufacturing solution, both production efficiency and product quality need to be considered. Specifically, the printing process is subject to constraints on print surface temperature to guarantee good product quality. In this paper, we propose a novel method for controlling layer time during the printing process by using thermal images. Specifically, several thin wall test components are printed by the Thermwood Large Scale Additive Manufacturing (LSAM™) machine, and the print surface temperature is monitored by a FLIR™ thermal camera. A regression model based on real-time thermal imaging data is built to predict the surface temperature. Then a layer time control method is proposed based on the temperature prediction model. By comparing the proposed method to the fixed layer time policy, the experiment results suggest that the control method by using real-time data can siginificantly reduce the layer time, and subsequently the total printing time, while satisfying the quality requirement.
UR - http://www.scopus.com/inward/record.url?scp=85072948021&partnerID=8YFLogxK
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U2 - 10.1109/COASE.2019.8843264
DO - 10.1109/COASE.2019.8843264
M3 - Conference contribution
AN - SCOPUS:85072948021
T3 - IEEE International Conference on Automation Science and Engineering
SP - 36
EP - 41
BT - 2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019
PB - IEEE Computer Society
T2 - 15th IEEE International Conference on Automation Science and Engineering, CASE 2019
Y2 - 22 August 2019 through 26 August 2019
ER -