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Application of Machine Learning in Statistical Process Control Charts: A Survey and Perspective

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Control Charts and Machine Learning for Anomaly Detection in Manufacturing

Part of the book series: Springer Series in Reliability Engineering ((RELIABILITY))

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Abstract

Over the past decades, control charts, one of the essential tools in Statistical Process Control (SPC), have been widely implemented in manufacturing industries as an effective approach for Anomaly Detection (AD). Thanks to the development of technologies like the Internet of Things (IoT) and Artificial Intelligence (AI), Smart Manufacturing (SM) has become an important concept for expressing the end goal of digitization in manufacturing. However, SM requires a more automatic procedure with capabilities to deal with huge data from the continuous and simultaneous process. Hence, traditional control charts of SPC now find difficulties in reality activities including designing, pattern recognition, and interpreting stages. Machine Learning (ML) algorithms have emerged as powerful analytic tools and great assistance that can be integrating to control charts of SPC to solve these issues. Therefore, the purpose of this chapter is first to presents a survey on the applications of ML techniques in the stages of designing, pattern recognition, and interpreting of control charts respectively in SPC especially in the context of SM for AD. Second, difficulties and challenges in these areas are discussed. Third, perspectives of ML techniques-based control charts for AD in SM are proposed. Finally, a case study of an ML-based control chart for bearing failure AD is also provided in this chapter.

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Authors and Affiliations

  1. International Research Institute for Artificial Intelligence and Data Science, Dong A University, Danang, Vietnam

    Phuong Hanh Tran, Thi Hien Nguyen & Kim Duc Tran

  2. Department of Statistics, Ferdowsi University of Mashhad, P. O. Box 1159, 91775, Mashhad, Iran

    Adel Ahmadi Nadi

  3. Laboratoire AGM, UMR CNRS 8088, CY Cergy Paris Université, 95000, Cergy, France

    Thi Hien Nguyen

  4. University of Lille, ENSAIT, GEMTEX, 59000, Lille, France

    Adel Ahmadi Nadi & Kim Phuc Tran

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  1. Phuong Hanh Tran
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  3. Thi Hien Nguyen
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  4. Kim Duc Tran
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  5. Kim Phuc Tran
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Correspondence to Kim Phuc Tran .

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    Kim Phuc Tran

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Tran, P.H., Ahmadi Nadi, A., Nguyen, T.H., Tran, K.D., Tran, K.P. (2022). Application of Machine Learning in Statistical Process Control Charts: A Survey and Perspective. In: Tran, K.P. (eds) Control Charts and Machine Learning for Anomaly Detection in Manufacturing. Springer Series in Reliability Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-83819-5_2

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