Diagnosis of Out-of-Control Signals in Complex Manufacturing Processes

  • Marcin PerzykEmail author
  • Jacek Kozlowski
  • Agnieszka Rodziewicz
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 183)


Some new perspectives of applications of advanced data-driven modeling in control and fault diagnosis of manufacturing processes are presented. The time-series analysis can help to identify and isolate autocorrelations in the process, being a source of misleading conclusions about the process disturbances. Learning systems such artificial neural networks and classification trees can be used in identification of non-standard out-of-control signals. Finding the root-cases of the process disturbances can be facilitated using advanced models linking the process inputs and process outputs.



The authors would like to thank prof. Jan Jezierski and prof. Jan Szajnar for the permission to use the copyrighted material from our three papers which appeared in Archives of Foundry Engineering.

We would also like to thank prof. Witold Bialy for the permission to use the copyrighted material from our chapter in the monograph “Systems Supporting Production Engineering”, published by PA NOVA SA. Gliwice, Poland in 2013 (ISBN 978-83-937845-0-9).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Marcin Perzyk
    • 1
    Email author
  • Jacek Kozlowski
    • 1
  • Agnieszka Rodziewicz
    • 1
  1. 1.Faculty of Production EngineeringWarsaw University of TechnologyWarsawPoland

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