Univariate process monitoring using multiscale Shewhart charts

M. Ziyan Sheriff, Fouzi Harrou, Mohamed Nounou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

Monitoring charts play an important role in statistical quality control. Shewhart charts are among the most commonly used charts in process monitoring, and have seen many extensions for improved performance. Unfortunately, measured practical data are usually contaminated with noise, which degrade the detection abilities of the conventional Shewhart chart by increasing the rate of false alarms. Therefore, the effect of noise needs to be suppressed for enhanced process monitoring. Wavelet-based multiscale representation of data, which is a powerful feature extraction tool, has shown good abilities to efficiently separate deterministic and stochastic features. In this paper, the advantages of multiscale representation are exploited to enhance the fault detection performance of the conventional Shewhart chart by developing an integrated multiscale Shewhart algorithm. The performance of the developed algorithm is illustrated using two examples, one using synthetic data, and the other using simulated distillation column data. The simulation results clearly show the effectiveness of the proposed method over the conventional Shewhart chart and the conventional Shewhart chart applied on multiscale pre-filtered data.

Original languageEnglish
Title of host publicationProceedings - 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages435-440
Number of pages6
ISBN (Electronic)9781479967735
DOIs
Publication statusPublished - 1 Jan 2014
Event2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014 - Metz, France
Duration: 3 Nov 20145 Nov 2014

Other

Other2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014
CountryFrance
CityMetz
Period3/11/145/11/14

Fingerprint

Process monitoring
Distillation columns
Fault detection
Quality control
Feature extraction
Control charts
Charts
Monitoring

Keywords

  • Filtering
  • Multiscale
  • Shewhart charts
  • Wavelets

ASJC Scopus subject areas

  • Information Systems and Management
  • Control and Systems Engineering

Cite this

Sheriff, M. Z., Harrou, F., & Nounou, M. (2014). Univariate process monitoring using multiscale Shewhart charts. In Proceedings - 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014 (pp. 435-440). [6996933] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CoDIT.2014.6996933

Univariate process monitoring using multiscale Shewhart charts. / Sheriff, M. Ziyan; Harrou, Fouzi; Nounou, Mohamed.

Proceedings - 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 435-440 6996933.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Sheriff, MZ, Harrou, F & Nounou, M 2014, Univariate process monitoring using multiscale Shewhart charts. in Proceedings - 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014., 6996933, Institute of Electrical and Electronics Engineers Inc., pp. 435-440, 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014, Metz, France, 3/11/14. https://doi.org/10.1109/CoDIT.2014.6996933
Sheriff MZ, Harrou F, Nounou M. Univariate process monitoring using multiscale Shewhart charts. In Proceedings - 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 435-440. 6996933 https://doi.org/10.1109/CoDIT.2014.6996933
Sheriff, M. Ziyan ; Harrou, Fouzi ; Nounou, Mohamed. / Univariate process monitoring using multiscale Shewhart charts. Proceedings - 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 435-440
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