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    Conclusion and further research directions

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    Type
    Book Chapter
    Authors
    Harrou, Fouzi cc
    Sun, Ying cc
    Hering, Amanda S.
    Madakyaru, Muddu
    Dairi, Abdelkader
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Statistics Program
    Date
    2021
    Embargo End Date
    2023-01-01
    Permanent link to this record
    http://hdl.handle.net/10754/667738
    
    Metadata
    Show full item record
    Abstract
    Developing efficient anomaly detection and isolation schemes that offer early detection of potential anomalies in the monitored process and identify and isolate the source of the detected anomalies is indispensable to monitor process operations in an efficient manner. This will further enhance availability, operation reliability, and profitability of monitored processes and reduce manpower costs. This book is mainly devoted to data-driven fault detection and isolation methods based on multivariate statistical monitoring techniques and deep learning methods. In this chapter, conclusions and further research directions are drawn.
    Citation
    Harrou, F., Sun, Y., Hering, A. S., Madakyaru, M., & Dairi, A. (2021). Conclusion and further research directions. Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches, 305–309. doi:10.1016/b978-0-12-819365-5.00015-2
    Publisher
    Elsevier BV
    ISBN
    9780128193655
    DOI
    10.1016/b978-0-12-819365-5.00015-2
    Additional Links
    https://linkinghub.elsevier.com/retrieve/pii/B9780128193655000152
    Relations
    Is Part Of:
    • [Book]
      Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches. (2021). doi:10.1016/c2018-0-05141-5. DOI: 10.1016/c2018-0-05141-5 Handle: 10754/667757
    ae974a485f413a2113503eed53cd6c53
    10.1016/b978-0-12-819365-5.00015-2
    Scopus Count
    Collections
    Book Chapters; Statistics Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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