Using IoT technology for computer-integrated manufacturing systems in the semiconductor industry

被引:29
作者
Chen, Yu-Qiang [1 ]
Zhou, Biao [2 ]
Zhang, Mingming [3 ]
Chen, Chien-Ming [4 ]
机构
[1] Dongguan Polytech, Dept Comp Engn, Dongguan 523808, Peoples R China
[2] Jiangnan Univ, IoT Engn Res Ctr Minist Educ, Wuxi 214122, Peoples R China
[3] Jiangnan Univ, Sch Digital Media, Wuxi 214122, Peoples R China
[4] Shandong Univ Sci & Technol, Coll Comp Sci & Engn, Qingdao, Shandong, Peoples R China
基金
中国国家自然科学基金;
关键词
Internet of Things (IoT); Radio Frequency Identification (RFID); Computer-Integrated Manufacturing (CIM); Feature Advantage Benefit (FAB); Manufacturing Execution System (MES); NEURAL-NETWORK; OPTIMIZATION; ALGORITHM;
D O I
10.1016/j.asoc.2020.106065
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The evolution of semiconductor manufacturing between lot and equipment has an increasingly complex relationship in the track-in/track-out process mechanism. Failure of reading or updating barcodes may cause some lots to scrap with mis-operation. In this paper, it proposed an Internet of Things (IoT) based Computer-Integrated Manufacturing (CIM) system used in Feature Advantage Benefit (FAB), that semiconductor company used Radio Frequency Identification (RFID) into 300-mm (FAB), and according to the information provided by the semiconductor company MTB (Manufacturing Technical Board). This solution to change the operation process flow to fit the CIM system characteristics of Fab in Manufacturing Execution System (MES). It also use IoT design strategy and the system architecture of this new IoT solution. The result of this research is to incorporate deep learning method in the IoT system into the current CIM system to reveal the benefits in FAB. It estimate to save about US$ 2.8M by adopting IoT RFID instead of tagging to identify a work in process lot in the initiation phase. The company can gain greater asset visibility, reduce the costs of man-power requirements and connect with the worldwide trend. (C) 2020 Elsevier B.V. All rights reserved.
引用
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页数:13
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