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Monitoring processes with data censored owing to competing risks by using exponentially weighted moving average control charts

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  • Stefan H. Steiner
  • R. Jock MacKay

Abstract

In industry, process monitoring is widely employed to detect process changes rapidly. However, in some industrial applications observations are censored. For example, when testing breaking strengths and failure times often a limited stress test is performed. With censored observations, a direct application of traditional monitoring procedures is not appropriate. When the censoring occurs due to competing risks, we propose a control chart based on conditional expected values to detect changes in the mean strength. To protect against possible confounding caused by changes in the mean of the censoring mechanism we also suggest a similar chart to detect changes in the mean censoring level. We provide an example of monitoring bond strength to illustrate the application of this methodology.

Suggested Citation

  • Stefan H. Steiner & R. Jock MacKay, 2001. "Monitoring processes with data censored owing to competing risks by using exponentially weighted moving average control charts," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 50(3), pages 293-302.
    • Handle: RePEc:bla:jorssc:v:50:y:2001:i:3:p:293-302
    DOI: 10.1111/1467-9876.00234
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    Cited by:

    1. Shervin Asadzadeh & Abdollah Aghaie & Seyed Niaki, 2013. "AFT regression-adjusted monitoring of reliability data in cascade processes," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(6), pages 3349-3362, October.
    2. Pei-Hsi Lee & Shih-Lung Liao, 2023. "Residual Control Chart Based on a Convolutional Neural Network and Support Vector Regression for Type-I Censored Data with the Weibull Model," Mathematics, MDPI, vol. 12(1), pages 1-14, December.

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