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.
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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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DOI: https://doi.org/10.1007/978-981-10-8168-2_6
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