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Multistage Manufacturing Processes: Innovations in Statistical Modeling and Inference

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Proceedings of the Pacific Rim Statistical Conference for Production Engineering

Part of the book series: ICSA Book Series in Statistics ((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.

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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.

Author information

Authors and Affiliations

  1. Institute of Statistics, National University of Kaohsiung, Kaohsiung, Taiwan, R.O.C.

    Hsiang-Ling Hsu & Shu-Hui Yu

  2. Institute of Statistics, National Tsing Hua University, Hsinchu, Taiwan, R.O.C.

    Ching-Kang Ing

  3. Department of Statistics, Stanford University, Stanford, CA, USA

    Tze Leung Lai

Authors
  1. Hsiang-Ling Hsu
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  2. Ching-Kang Ing
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  3. Tze Leung Lai
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  4. Shu-Hui Yu
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Corresponding author

Correspondence to Hsiang-Ling Hsu .

Editor information

Editors and Affiliations

  1. Oregon Health & Science University , Portland, Oregon, USA

    Dongseok Choi

  2. Pukyong National University , Busan, Korea (Republic of)

    Daeheung Jang

  3. Stanford University, Stanford, California, USA

    Tze Leung Lai

  4. Seoul National University, Gwanak-gu, Seoul, Korea (Republic of)

    Youngjo Lee

  5. Stanford University , Stanford, California, USA

    Ying Lu

  6. University of Michigan–Ann Arbor, Ann Arbor, Michigan, USA

    Jun Ni

  7. University of Wisconsin–Madison, Madison, Wisconsin, USA

    Peter Qian

  8. University of Florida, Gainesville, Florida, USA

    Peihua Qiu

  9. University of Chicago , Chicago, Illinois, USA

    George Tiao

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Hsu, HL., Ing, CK., Lai, T.L., Yu, SH. (2018). Multistage Manufacturing Processes: Innovations in Statistical Modeling and Inference. In: Choi, D., et al. Proceedings of the Pacific Rim Statistical Conference for Production Engineering. ICSA Book Series in Statistics. Springer, Singapore. https://doi.org/10.1007/978-981-10-8168-2_6

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