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Advances in Intelligent Information Hiding and Multimedia Signal Processing pp 41–49Cite as

Study on IoT and Big Data Analysis of Furnace Process Exhaust Gas Leakage

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 156))

Abstract

Modern FABs use a large number of high-energy processes such as plasma, CVD, and ion implantation; the furnace is one of the important tools of semiconductor manufacturing. The FAB installed FTIR system due to the 12” furnace tools based on the aforementioned production management requirements. This study used open-type FTIR and integrated IoT mechanism to connect to the cloud, which is suitable for a variety of gaseous pollutants. This study set up two measuring points of furnace process tools in the 12” factory of Hsinchu Science Park in Taiwan. This study obtained FTIR measurements, and according to the OHSA regulations, this study is set in the cloud database for big data analysis and decision-making, when the upper limits of TEOS, C2H4, and CO are 0.6 ppm, 2.0 ppm, and 1.7 ppm and the lower limits of TEOS, C2H4, and CO are 0.4 ppm, 1.5 ppm, and 1 ppm. The application architecture of this study can be extended to other semiconductor processes, so that IoT integration and big data operations can be performed for all processes; this is an important step in promoting FAB intelligent production and an important contribution of this study.

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Author information

Authors and Affiliations

  1. Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, China

    Yu-Wen Zhou, Kuo-Chi Chang, Jeng-Shyang Pan & Yuh-Chung Lin

  2. Department of Business Administration Group of Strategic Management, National Central University, Taoyuan, Taiwan

    Kai-Chun Chu & Der-Juinn Horng

  3. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, China

    Huang Jing

Authors
  1. Yu-Wen Zhou
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  2. Kuo-Chi Chang
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  3. Jeng-Shyang Pan
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  4. Kai-Chun Chu
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  5. Der-Juinn Horng
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  6. Yuh-Chung Lin
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  7. Huang Jing
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Corresponding author

Correspondence to Kuo-Chi Chang .

Editor information

Editors and Affiliations

  1. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao Shi, Shandong, China

    Jeng-Shyang Pan

  2. Northeast Electric Power University, Chuanying Qu, Jilin, China

    Jianpo Li

  3. Swinburne University of Technology, Hawthorn, Melbourne, Australia

    Pei-Wei Tsai

  4. Centre for Artificial Intelligence, University of Technology Sydney, Sydney, NSW, Australia

    Lakhmi C. Jain

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Cite this paper

Zhou, YW. et al. (2020). Study on IoT and Big Data Analysis of Furnace Process Exhaust Gas Leakage. In: Pan, JS., Li, J., Tsai, PW., Jain, L. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. Smart Innovation, Systems and Technologies, vol 156. Springer, Singapore. https://doi.org/10.1007/978-981-13-9714-1_5

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