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Wavelet-Based Profile Monitoring Using Order-Thresholding Recursive CUSUM Schemes

  • Ruizhi Zhang
  • Yajun Mei
  • Jianjun Shi
Chapter
Part of the ICSA Book Series in Statistics book series (ICSABSS)

Abstract

With the rapid development of advanced sensing technologies, rich and complex real-time profile or curve data are available in many processes in biomedical sciences and manufacturing. These profile data provide valuable intrinsic information about the performance or properties of the process, subject, or product, and it is often desirable to utilize them to develop efficient methodologies for process monitoring and fault diagnosing. In this article, we propose a novel wavelet-based profile monitoring procedure that is based on the order-thresholding transformation of recursive CUSUM statistics of multiple wavelet coefficients. Extensive simulation studies and a case study of tonnage profile data demonstrate that our proposed procedure is efficient for detecting the unknown local changes on the profile.

Notes

Acknowledgements

This research is partially supported by NSF grant CMMI-1362876.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.H. Milton Stewart School of Industrial and Systems EngineeringGeorgia Institute of TechnologyAtlantaUSA

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