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A two-sided sequential probability ratio test (SPRT) control chart for monitoring the mean of a normal process is proposed in this paper. Its mechanism is based on the SPRT for the mean of a normal distribution that is extended for a two-sided alternative. The exact statistical performance measures of this chart are obtained using a Markov chain approach. An approach to design the chart such that it has a specified in-control performance and the optimal out-of-control performance for detecting a mean shift of a particular size is provided. The statistical performance of this chart is numerically compared with that of various competing charts in the existing literature. It is found that the proposed chart outperforms all these charts for detecting a mean shift of any size. An example to illustrate the mechanism of the chart is provided. [ABSTRACT FROM AUTHOR]

A Shewhart control chart is highly effective for detecting large process shifts, however, it is relatively less sensitive to the small shifts. A CUSUM chart is more efficient than a Shewhart chart for detecting small process shifts but it is inferior to that for detecting the large ones. This paper proposes the nonparametric combined Shewhart-CUSUM (CSC) control charts based on the sign statistic. By appropriately choosing the design parameters, a CSC chart exhibits a trade-off statistical performance between that of the Shewhart and CUSUM sign charts. That is, its performance lies between the performances of the Shewhart and CUSUM sign charts for detecting a process shift of any size. The expressions for the zero-state and steady-state average run lengths of the CSC chart are obtained using a Markov chain approach. An example illustrating the implementation of this chart is provided. [ABSTRACT FROM AUTHOR]

Maxwell distribution has several applications in modeling physical and chemical processes, as well as in reliability and lifetime data analysis. In this paper, we propose the one‐ and two‐sided SPRT control charts for monitoring the scale parameter of a Maxwell distributed process. Using a Markov chain approach, we obtain the measures of statistical performance for the one‐sided charts. Reasonably accurate relationships between the performance measures of a two‐sided SPRT chart and that of its corresponding one‐sided charts are derived through Monte‐Carlo simulations. Approaches for designing the one‐ and two‐sided SPRT charts having the specified in‐control and the optimal out‐of‐control performances are provided. The results of the numerical study reveal that the proposed charts significantly outperform the Shewhart and cumulative sum (CUSUM) charts for detecting a shift of any size in the scale parameter. The mechanisms of the one‐ and two‐sided SPRT charts are illustrated via two real‐data examples: the first in the monitoring of the urinary glycosaminoglycan concentration and the second in the monitoring of the bearing life. [ABSTRACT FROM AUTHOR]

This paper investigates the statistical performance of a sequential probability ratio test control chart for monitoring the dispersion of a normally distributed process. The expressions for statistical performance measures of the chart are derived using a Markov chain approach. It is shown through numerical comparisons that the overall statistical performance of this chart is superior to that of the existing competitor charts for dispersion. An example illustrating an application of the chart in practice is provided. [ABSTRACT FROM AUTHOR]