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Multivariate adaptive approach for monitoring simple linear profiles

Author

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  • Galal M. Abdella
  • Kai Yang
  • Adel Alaeddini

Abstract

Adaptive sample size and sampling intervals schemes have been widely used to improve the statistical efficiency of Hotelling T² control chart in detecting small changes when the quality of a product or a process can be characterised by the multivariate distribution of quality characteristics. In this paper, we design a Hotelling T² scheme varying sample sizes and sampling intervals (VSSI-T²) for accelerating the speed of detecting off-target conditions in linear profile parameters. We investigate the statistical performance of the adaptive approach versus its fixed sampling counterparts. To find the optimal setting of the VSSI-T², we build an optimisation model solved using genetic algorithm (GA). Also, average time to signal (ATS) is considered as the objective function of the model and estimated using the Markov chain fundamentals. The comparative studies reveal the potentials of the adaptive scheme in improving the performance of the Hotelling T² control chart in monitoring linear profiles.

Suggested Citation

  • Galal M. Abdella & Kai Yang & Adel Alaeddini, 2014. "Multivariate adaptive approach for monitoring simple linear profiles," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 6(1), pages 2-14.
    • Handle: RePEc:ids:injdan:v:6:y:2014:i:1:p:2-14
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    Cited by:

    1. Nuri Cihat Onat & Galal M. Abdella & Murat Kucukvar & Adeeb A. Kutty & Munera Al‐Nuaimi & Gürkan Kumbaroğlu & Melih Bulu, 2021. "How eco‐efficient are electric vehicles across Europe? A regionalized life cycle assessment‐based eco‐efficiency analysis," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(5), pages 941-956, September.
    2. Men, Tianli & Li, Yan-Fu & Ji, Yujun & Zhang, Xinliang & Liu, Pengfei, 2022. "Health assessment of high-speed train wheels based on group-profile data," Reliability Engineering and System Safety, Elsevier, vol. 223(C).

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