A variable sampling interval EWMA control chart for urinary tract infections data

Abstract

Control chart is an important method in Statistical Process Control, which is used to study how a process changes over time. The exponential distribution is one of the commonly used models for fitting data, especially in areas such as component life, aviation accidents, or health-care processes. In order to further improve the sensitivity of the control chart, we propose an exponentially weighted moving average control chart with a variable sampling interval scheme, denoted as VSIEWMA-T control chart, for monitoring exponentially distributed quality characteristics (e.g. Urinary Tract Infections data). In this paper, the average time to signal property of the proposed control chart is investigated using the Markov chain method. In addition, parameter optimization algorithms for known or unknown shift levels are provided. Subsequently, numerical analysis shows that the proposed control chart outperforms other competitive control charts. Finally, an example of urinary tract infections data is provided for illustration.

KEYWORDS:

• Exponentially weighted moving average chart
• variable sampling interval
• exponential distribution
• Markov chain method
• optimization algorithms

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Fundamental Research Funds for the Central Universities: [grant no JBK2201058]; Hainan Provincial Natural Science Foundation of China: [grant no 522QN283].