Multistage Manufacturing Processes: Innovations in Statistical Modeling and Inference

  • Hsiang-Ling Hsu
  • Ching-Kang Ing
  • Tze Leung Lai
  • Shu-Hui Yu
Conference paper
Part of the ICSA Book Series in Statistics book series (ICSABSS)

Abstract

Modeling multistage manufacturing processes for fault detection and diagnosis in modern production systems has emerged as a cutting-edge research area at the interface of the engineering and statistical sciences. We give an overview of the developments in this area and describe some recent innovations in statistical modeling and inference associated with these developments.

Notes

Acknowledgements

Hsu’s research was partially supported by the Ministry of Science and Technology of Taiwan under grant MOST 105-2118-M-390-004. Ing’s research was supported by the Science Vanguard Research Program, Ministry of Science and Technology, Taiwan. Lai’s research was supported by National Science Foundation grant DMS-1407828. Yu’s research was partially supported by the Ministry of Science and Technology of Taiwan under grant MOST 105-2118-M-390-001.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Hsiang-Ling Hsu
    • 1
  • Ching-Kang Ing
    • 2
  • Tze Leung Lai
    • 3
  • Shu-Hui Yu
    • 1
  1. 1.Institute of StatisticsNational University of KaohsiungKaohsiungTaiwan, R.O.C.
  2. 2.Institute of StatisticsNational Tsing Hua UniversityHsinchuTaiwan, R.O.C.
  3. 3.Department of StatisticsStanford UniversityStanfordUSA

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