Titlebook: Artificial Intelligence for Smart Manufacturing; Methods, Application Kim Phuc Tran Book 2023 The Editor(s) (if applicable) and The Author(

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https://doi.org/10.1007/978-3-322-93671-4ontrol (SPC) problems, the existing machine learning approaches have some limitations. For instance, most of them are designed for cases in which in-control (IC) process observations at different time points are assumed to be independent and identically distributed. In practice, however, serial corr

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https://doi.org/10.1007/978-3-322-93671-4ocess and the high risk derived from severe consequences on the paper mills in case of production failure. Whereas the paper manufacturing process is continuous that is difficult to be warned early of faults. To address such issues, this Chapter proposes a data-driven approach to predict fault in th

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