PredNet and CompNet: Prediction and High-Precision Compensation of In-Plane Shape Deformation for Additive Manufacturing

CASIA OpenIR > 复杂系统管理与控制国家重点实验室 > 平行智能技术与系统团队

	PredNet and CompNet: Prediction and High-Precision Compensation of In-Plane Shape Deformation for Additive Manufacturing
	Shen, Zhen1,2 ; Shang, Xiuqin1,2 ; Li, Yuqing 4; Bao, Yin 1; Zhang, Xipeng 5; Dong, Xisong 6; Wan, Li 7; Xiong, Gang1,2,3 ; Wang, Fei-Yue1,2
	2019-08-22
Conference Name	2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)
Conference Date	August 22-26, 2019
Conference Place	Vancouver, BC, Canada
Publisher	2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)
Abstract	The error compensation for printed objects in additive manufacturing (AM) has always been one of the most critical problems. The precision control of the AM is usually more difficult than the subtractive manufacturing system, whose precision can reach the micron level easily by using a servo system. For the AM, there usually exist shrinkage and curling effects which lead to deformation. In this paper, we focus on the in-plane shape deformation problem, and we build the PredNet and CompNet, using deep neural networks for the error prediction and compensation. We test our methods on dental crown models. We generate deformed models by simulation of the translation, scaling down and rotation deformation. The minimum F1 scores of error prediction and compensation can be up to 0.982.
Indexed By	EI
Funding Project	Guangdong Science and Technology Department[2016B090910001] ; China Guangdong's ST Project[2017B090912001] ; National Natural Science Foundation of China[61533019] ; National Natural Science Foundation of China[61773381] ; National Natural Science Foundation of China[61773382] ; National Natural Science Foundation of China[61773382] ; National Natural Science Foundation of China[61773381] ; National Natural Science Foundation of China[61533019] ; China Guangdong's ST Project[2017B090912001] ; Guangdong Science and Technology Department[2016B090910001]
Sub direction classification	人工智能+制造
Document Type	会议论文
Identifier	http://ir.ia.ac.cn/handle/173211/26150
Collection	复杂系统管理与控制国家重点实验室_平行智能技术与系统团队
Corresponding Author	Xiong, Gang
Affiliation	1.the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences 2.Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences 3.the Cloud Computing Center, Chinese Academy of Sciences 4.the University of Southern California 5.the School of Computer and Control Engineering, University of Chinese Academy of Sciences 6.the Qingdao Academy of Intelligent Industries 7.Beijing Ten Dimensions Technology Co., Ltd
First Author Affilication	Institute of Automation, Chinese Academy of Sciences
Corresponding Author Affilication	Institute of Automation, Chinese Academy of Sciences
Recommended Citation GB/T 7714	Shen, Zhen,Shang, Xiuqin,Li, Yuqing,et al. PredNet and CompNet: Prediction and High-Precision Compensation of In-Plane Shape Deformation for Additive Manufacturing[C]:2019 IEEE 15th International Conference on Automation Science and Engineering (CASE),2019.

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