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International Conference on Advanced Machine Learning Technologies and Applications

AMLTA 2021: Advanced Machine Learning Technologies and Applications pp 514–524Cite as

Study of the Degree of Automation of High-Tech Smart Factory: Taiwan 12” Semiconductor Factory Case Study

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1339))

Abstract

The globalization of Taiwan's corporate industries is subject to competition and threats at two critical levels. Taiwan's factories could use Industry 4.0 to enhance their competitiveness. This listing Taiwanese semiconductor manufacturing factory Hsinchu A, B conducts industrial maturity assessment analysis of automation equipment. This study shows that the existing equipment automation in Factory A is 1.20, the ideal is 2.74, the average is 1.65, and the proportion of artificial is 80%, which is much higher than the industry average of 42%. The actual value of equipment automation in Factory B is 2.96, and the ideal is 2.76. The standard is 1.67, fully automatic, accounted for 100%, much higher than the industry average of 15%. The automation of the equipment evaluation project shows the average value of the leading industry self-evaluation. Finally, although this equipment's operation has been relatively smooth, we must pay attention to the industry's future trends and promptly improve it.

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Author information

Authors and Affiliations

  1. School of Management, Fujian University of Technology, Fuzhou, China

    Kai-Chun Chu, Yuh-Chung Lin, Nguyen Trong-The & Tien-Wen Sung

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

    Kuo-Chi Chang, Yuh-Chung Lin, Nguyen Trong-The & Tien-Wen Sung

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

    Kuo-Chi Chang

  4. Department of Tourism, Shih-Hsin University, Taipei, Taiwan

    Fu-Hsiang Chang

  5. Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan

    Hsiao-Chuan Wang

  6. Institute of Construction Engineering and Management, National Central University, Taoyuan, Taiwan

    Tsui-Lien Hsu

  7. College of Mechanical and Electrical Engineering, National Taipei University of Technology, Taipei, Taiwan

    Kuo-Chi Chang

  8. Department of Business Administration, North Borneo University College, Sabah, Malaysia

    Kuo-Chi Chang

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

    Kai-Chun Chu

Authors
  1. Kai-Chun Chu
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  2. Kuo-Chi Chang
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  3. Fu-Hsiang Chang
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  4. Hsiao-Chuan Wang
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  5. Yuh-Chung Lin
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  6. Tsui-Lien Hsu
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  7. Nguyen Trong-The
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  8. Tien-Wen Sung
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Corresponding author

Correspondence to Kuo-Chi Chang .

Editor information

Editors and Affiliations

  1. Information Technology Department, Cairo University, Computer and Information Faculty, Giza, Egypt

    Aboul-Ella Hassanien

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

    Kuo-Chi Chang

  3. International Center for Informatics Research, Beijing Jaiotong University, Beijing, China

    Tang Mincong

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Chu, KC. et al. (2021). Study of the Degree of Automation of High-Tech Smart Factory: Taiwan 12” Semiconductor Factory Case Study. In: Hassanien, AE., Chang, KC., Mincong, T. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2021. Advances in Intelligent Systems and Computing, vol 1339. Springer, Cham. https://doi.org/10.1007/978-3-030-69717-4_49

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