ACS Publications. Most Trusted. Most Cited. Most Read
My Activity

Figure 1Loading Img

Nearest Neighbors Methods for Root Cause Analysis of Plantwide Disturbances

View Author Information
Department of Electronic and Electrical Engineering, University College London, London WC1E 7JE, United Kingdom, Eastman Chemical Company, Advanced Controls Technology Group, Kingsport, Tennessee 37662-5280, and Department of Chemical Engineering, Imperial College London, London SW7 2AZ, United Kingdom
Cite this: Ind. Eng. Chem. Res. 2007, 46, 18, 5977–5984
Publication Date (Web):July 31, 2007
Copyright © 2007 American Chemical Society

    Article Views





    Other access options


    In continuous chemical processes, disturbances travel along propagation paths in the direction of the control path or process flow. This article applies a method based on the nearest neighbors of embedded vectors to historical process data for the purpose of identifying the direction of propagation of disturbances. The resulting measure is sensitive to directionality even in the absence of an observable time delay. Its performance is studied in two industrial case studies, and default settings for the parameters in the algorithm are derived so that it can be applied in a large scale setting.

    Read this article

    To access this article, please review the available access options below.

    Get instant access

    Purchase Access

    Read this article for 48 hours. Check out below using your ACS ID or as a guest.


    Access through Your Institution

    You may have access to this article through your institution.

    Your institution does not have access to this content. You can change your affiliated institution below.

     University College London.

     Eastman Chemical Company.


     To whom correspondence should be addressed. Tel.:  020 7594 6622. E-mail:  [email protected].


     Imperial College London.

    Cited By

    This article is cited by 31 publications.

    1. Wahiba Bounoua, Muhammad Faisal Aftab, Christian Walter Peter Omlin. Controller Performance Monitoring: A Survey of Problems and a Review of Approaches from a Data-Driven Perspective with a Focus on Oscillations Detection and Diagnosis. Industrial & Engineering Chemistry Research 2022, 61 (49) , 17735-17765.
    2. Rohit S. Patwardhan, Hamza A. Hamadah, Kalpesh M. Patel, Rayan H. Hafiz, Majid M. Al-Gwaiz. Applications of Advanced Analytics at Saudi Aramco: A Practitioners’ Perspective. Industrial & Engineering Chemistry Research 2019, 58 (26) , 11338-11351.
    3. Shu Xu, Michael Baldea, Thomas F. Edgar, Willy Wojsznis, Terrence Blevins, and Mark Nixon . Root Cause Diagnosis of Plant-Wide Oscillations Based on Information Transfer in the Frequency Domain. Industrial & Engineering Chemistry Research 2016, 55 (6) , 1623-1629.
    4. Harikrishna Rao Mohan Rao, Sirish L. Shah, Tongwen Chen. Application of Alarm Correlations in Root Cause Diagnosis of Plant-wide Oscillations*. IFAC-PapersOnLine 2023, 56 (2) , 7154-7159.
    5. Bixian Zhang. Root Cause Analysis of Communication Network Based on Deep Fuzzy Neural Network. IEEE Access 2023, 11 , 135855-135863.
    6. Haniyeh Seyed Alinezhad, Mohammad Hossein Roohi, Tongwen Chen. A review of alarm root cause analysis in process industries: Common methods, recent research status and challenges. Chemical Engineering Research and Design 2022, 188 , 846-860.
    7. Matthieu Lucke, Moncef Chioua, Nina F. Thornhill. From oscillatory to non-oscillatory disturbances: A comparative review of root cause analysis methods. Journal of Process Control 2022, 113 , 42-67.
    8. Yinghua Yang, Weiqi Kang, Xiaozhi Liu. Fault diagnosis based on online dynamic integration model and transfer entropy. Measurement 2022, 193 , 110946.
    9. R. Landman, S.-L. Jämsä-Jounela. Hybrid causal analysis combining a nonparametric multiplicative regression causality estimator with process connectivity information. Control Engineering Practice 2019, 93 , 104140.
    10. Rinat Landman, Sirkka-Liisa Jamsa-Jounela. Fault Propagation Analysis by Implementing Nearest Neighbors Method Using Process Connectivity. IEEE Transactions on Control Systems Technology 2019, 27 (5) , 2058-2067.
    11. Zhiwen Chen, Yue Cao, Steven X. Ding, Kai Zhang, Tim Koenings, Tao Peng, Chunhua Yang, Weihua Gui. A Distributed Canonical Correlation Analysis-Based Fault Detection Method for Plant-Wide Process Monitoring. IEEE Transactions on Industrial Informatics 2019, 15 (5) , 2710-2720.
    12. Rongxi Wang, Jianmin Gao, Zhiyong Gao, Xu Gao, Hongquan Jiang, Zeming Liang. Interaction analysis–based information modeling of complex electromechanical systems in the processing industry. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 2017, 231 (8) , 638-651.
    13. Muhammad Faisal Aftab, Morten Hovd, Selvanathan Sivalingam. Convergent cross mapping (CCM) based approach for isolating the source of plant-wide disturbances. 2017, 1492-1498.
    14. Shiliang Fan, Yubin Yang, Wenyang Lu, Ping Song. Distributed Data Mining for Root Causes of KPI Faults in Wireless Networks. 2017, 201-209.
    15. Inês M. Cecílio, James R. Ottewill, Harald Fretheim, Nina F. Thornhill. Removal of transient disturbances from oscillating measurements using nearest neighbors imputation. Journal of Process Control 2016, 44 , 68-78.
    16. Inês M. Cecílio, James R. Ottewill, Nina F. Thornhill. Determining the propagation path of a disturbance in multi-rate process and electromechanical systems. Control Engineering Practice 2016, 49 , 187-193.
    17. Zhiqiang Ge, Junghui Chen. Plant-Wide Industrial Process Monitoring: A Distributed Modeling Framework. IEEE Transactions on Industrial Informatics 2016, 12 (1) , 310-321.
    18. Weijun Yu, Fan Yang. Detection of Causality between Process Variables Based on Industrial Alarm Data Using Transfer Entropy. Entropy 2015, 17 (12) , 5868-5887.
    19. Ping Duan, Fan Yang, Sirish L. Shah, Tongwen Chen. Transfer Zero-Entropy and Its Application for Capturing Cause and Effect Relationship Between Variables. IEEE Transactions on Control Systems Technology 2015, 23 (3) , 855-867.
    20. Prabal Mahanta, Saurabh Jain. Determination of Manufacturing Unit Root-Cause Analysis Based on Conditional Monitoring Parameters Using In-Memory Paradigm and Data-Hub Rule Based Optimization Platform. 2015, 41-48.
    21. Inês M. Cecílio, James R. Ottewill, Nina F. Thornhill. Determining the propagation path of a disturbance in multi-rate systems ★ ★The authors gratefully acknowledge the financial support from the Portuguese Foundation for Science and Technology (FCT) under Fellowship SFRH/BD/61384/2009 and the Marie Curie FP7-IAPP project “REAL-SMART - Using real-time measurements for monitoring and management of power transmission dynamics for the Smart Grid”, Contract No: PIAP-GA-2009-251304.. IFAC-PapersOnLine 2015, 48 (21) , 784-789.
    22. Ping Duan, Tongwen Chen, Sirish L. Shah, Fan Yang. Methods for root cause diagnosis of plant‐wide oscillations. AIChE Journal 2014, 60 (6) , 2019-2034.
    23. Zhiqiang Ge. Improved two-level monitoring system for plant-wide processes. Chemometrics and Intelligent Laboratory Systems 2014, 132 , 141-151.
    24. L.F. Recalde, R. Katebi, H. Yue. Sequential Control Performance Diagnosis of Steel Processes. IFAC Proceedings Volumes 2014, 47 (3) , 2830-2835.
    25. Ping Duan, Fan Yang, Tongwen Chen, Sirish L. Shah. Direct Causality Detection via the Transfer Entropy Approach. IEEE Transactions on Control Systems Technology 2013, 21 (6) , 2052-2066.
    26. Jie Yu, Mudassir M. Rashid. A novel dynamic bayesian network‐based networked process monitoring approach for fault detection, propagation identification, and root cause diagnosis. AIChE Journal 2013, 59 (7) , 2348-2365.
    27. Anna Lindholm, Charlotta Johnsson. Plant-wide utility disturbance management in the process industry. Computers & Chemical Engineering 2013, 49 , 146-157.
    28. Y. Shardt, Y. Zhao, F. Qi, K. Lee, X. Yu, B. Huang, S. Shah. Determining the state of a process control system: Current trends and future challenges. The Canadian Journal of Chemical Engineering 2012, 90 (2) , 217-245.
    29. James J. Downs, Michelle H. Caveness. Influence of Process Variability Propagation in Plantwide Control. 2012, 147-177.
    30. Markus Stockmann, Robert Haber, Ulrich Schmitz. Source identification of plant-wide faults based on k nearest neighbor time delay estimation. Journal of Process Control 2012, 22 (3) , 583-598.
    31. Anna Lindholm, Hampus Carlsson, Charlotta Johnsson. A General Method for Handling Disturbances on Utilities in the Process Industry. IFAC Proceedings Volumes 2011, 44 (1) , 2761-2766.

    Pair your accounts.

    Export articles to Mendeley

    Get article recommendations from ACS based on references in your Mendeley library.

    Pair your accounts.

    Export articles to Mendeley

    Get article recommendations from ACS based on references in your Mendeley library.

    You’ve supercharged your research process with ACS and Mendeley!

    STEP 1:
    Click to create an ACS ID

    Please note: If you switch to a different device, you may be asked to login again with only your ACS ID.

    Please note: If you switch to a different device, you may be asked to login again with only your ACS ID.

    Please note: If you switch to a different device, you may be asked to login again with only your ACS ID.

    Your Mendeley pairing has expired. Please reconnect