**5. Conclusion and suggestion**

In order to achieve high precision and yield, 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. The principle of measurement is the same as the principle of Extractive FTIR, but the closed cavity is changed to open type and integrated IoT mechanism to connect to the cloud, which is suitable for a variety of gaseous pollutants (including organic gases and inorganic gaseous pollutants) in the atmosphere are monitored in this study. 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 limit of TEOS, C2H4, CO are 0.6, 2.0, 1.7 ppm; the lower limit of TEOS, C2H4, CO is 0.4 , 1.5, 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.

**Author details**

Technology, Taiwan

University, Taiwan

**95**

Kuo-Chi Chang1,2\*, Kai-Chun Chu1

Tsui-Lien Hsu<sup>4</sup> and Yu-Wen Zhou<sup>1</sup>

1 Fujian University of Technology, China

*DOI: http://dx.doi.org/10.5772/intechopen.92849*

provided the original work is properly cited.

, Hsiao-Chuan Wang<sup>3</sup>

2 College of Mechanical and Electrical Engineering, National Taipei University of

*Study on IoT and Big Data Analysis of 12" 7 nm Advanced Furnace Process Exhaust Gas Leakage*

3 Institute of Environmental Engineering, National Taiwan University, Taiwan

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

4 Institute of Construction Engineering and Management, National Central

\*Address all correspondence to: albertchangxuite@gmail.com

, Yuh-Chung Lin1

,

*Study on IoT and Big Data Analysis of 12" 7 nm Advanced Furnace Process Exhaust Gas Leakage DOI: http://dx.doi.org/10.5772/intechopen.92849*
