Process Monitoring, Diagnosis and Control of Additive Manufacturing
文献类型：期刊论文
| 作者 | Fang, Qihang6,7; Xiong, Gang5,7 ; Zhou, MengChu3,4; Tamir, Tariku Sinshaw6,7; Yan, Chao-Bo1,2; Wu, Huaiyu5,7; Shen, Zhen5,7; Wang, Fei-Yue5,7
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| 刊名 | IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
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| 出版日期 | 2022-11-14 |
| 页码 | 27 |
| ISSN号 | 1545-5955 |
| 关键词 | Additive manufacturing (AM) in-situ monitoring defect detection fault diagnosis closed-loop control |
| DOI | 10.1109/TASE.2022.3215258 |
| 通讯作者 | Shen, Zhen(zhen.shen@ia.ac.cn) |
| 英文摘要 | Additive manufacturing (AM) can build up complex parts in a layer-by-layer manner, which is a kind of novel and flexible production technology. The special manufacturing capability of AM shows great application potential in various fields. However, an open-loop control method cannot guarantee the reliability and repeatability of an AM process. Defects often occur to deteriorate product quality and lead to material and time waste, which hinders the development of AM industry. In this regard, a lot of efforts have been made to make an AM process more controllable. This work proposes an AM control framework that divides the related studies into three feedback loops, including the in-situ monitoring of process defects, fault diagnosis of 3-D printers, and closed-loop control of an AM process. These three loops constitute the inspection and control of AM from the machine level to product level. Specifically, the measurement requirements for monitoring techniques, defect detection, fault diagnosis, and closed-loop control are summarized. The challenges and future trends in realizing a more reliable and repeatable AM process are discussed. Note to Practitioners-This survey is motivated by urgent need to solve product quality problems in additive manufacturing (AM) caused by open-loop control. Three feedback loops can be established to solve them. The first one is defect detection that inspects part quality during fabrication. The second one is the fault diagnosis of a 3-D printer that monitors the health and operation conditions of its actuators. The last one is closed-loop control that improves AM process reliability and repeatability by regulating process variables in real time. These three loops are all based on the feedback signals of in-situ monitoring systems. This paper reviews the related studies and provides guidance for establishing the monitoring systems, performing defect detection and fault diagnosis, and designing closed-loop control systems, which helps realize more reliable and repeatable AM. |
| WOS关键词 | CONVOLUTIONAL NEURAL-NETWORK ; ITERATIVE LEARNING CONTROL ; LASER MELTING PROCESS ; IN-SITU MEASUREMENTS ; CLOSED-LOOP CONTROL ; FUSION AM PROCESS ; METAL-DEPOSITION ; DEFECT DETECTION ; FAULT-DIAGNOSIS ; QUALITY-CONTROL |
| 资助项目 | National Key Research and Development Program of China[2018YFB1702700] ; National Natural Science Foundation of China[U1909204] ; National Natural Science Foundation of China[U1909218] ; Scientific Instrument Developing Project of the Chinese Academy of Sciences (CAS)[YZQT014] ; Guangdong Basic and Applied Basic Research Foundation[2021B1515140034] ; Foshan Science and Technology Innovation Team Project[2018IT100142] ; Youth Foundation of the State Key Laboratory for Management and Control of Complex Systems[Y6S9011F1G] ; Fundo para o Desenvolvimento das Ciencias e da Tecnologia (FDCT)[0047/2021/A1] ; CAS Science and Technology Service Network Initiative (STS) Dongguan Joint Project[20201600200072] ; CAS Key Technology Talent Program |
| WOS研究方向 | Automation & Control Systems |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:000886928200001 |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Scientific Instrument Developing Project of the Chinese Academy of Sciences (CAS) ; Guangdong Basic and Applied Basic Research Foundation ; Foshan Science and Technology Innovation Team Project ; Youth Foundation of the State Key Laboratory for Management and Control of Complex Systems ; Fundo para o Desenvolvimento das Ciencias e da Tecnologia (FDCT) ; CAS Science and Technology Service Network Initiative (STS) Dongguan Joint Project ; CAS Key Technology Talent Program |
| 源URL | [http://ir.ia.ac.cn/handle/173211/51254]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队 |
| 通讯作者 | Shen, Zhen |
| 作者单位 | 1.Xi An Jiao Tong Univ, Fac Elect & Informat Engn, Sch Automation Sci & Engn, Xian 710049, Shaanxi, Peoples R China 2.Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian 710049, Shaanxi, Peoples R China 3.Macau Univ Sci & Technol, Inst Syst Engn, Macau 999078, Peoples R China 4.New Jersey Inst Technol, Dept Elect & Comp Engn, Newark, NJ 07102 USA 5.Chinese Acad Sci, Guangdong Engn Res Ctr 3D Printing & Intelligent M, Cloud Comp Ctr, Dongguan 523808, Peoples R China 6.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 7.Chinese Acad Sci, Inst Automat, Beijing Engn Res Ctr Intelligent Syst & Technol, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Fang, Qihang,Xiong, Gang,Zhou, MengChu,et al. Process Monitoring, Diagnosis and Control of Additive Manufacturing[J]. IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING,2022:27. |
| APA | Fang, Qihang.,Xiong, Gang.,Zhou, MengChu.,Tamir, Tariku Sinshaw.,Yan, Chao-Bo.,...&Wang, Fei-Yue.(2022).Process Monitoring, Diagnosis and Control of Additive Manufacturing.IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING,27. |
| MLA | Fang, Qihang,et al."Process Monitoring, Diagnosis and Control of Additive Manufacturing".IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2022):27. |
入库方式： OAI收割
来源：自动化研究所
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