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A design algorithm is proposed to develop the optimal SPRT chart for monitoring the fraction nonconforming p of Bernoulli processes.
Based on these results, we propose the jumps control chart for monitoring a binomial AR(1) process.
This paper proposes a synthetic control chart for monitoring the changes in the standard deviation of a normally distributed process.
This article proposes a Generalized CRL chart (namely GCRL chart) for monitoring the mean of a measurable quality characteristic x under 100% inspection.
This paper proposes an economic model for the design of an SPRT (Sequential Probability Ratio Test) chart for monitoring the process mean in short-run production.
This paper develops a control chart for monitoring the process mean that is based on applying a sequential probability ratio test (SPRT) to the observations at each sampling point.
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In this article, we propose a new t-chart for monitoring a process under the assumption that the time between events follows the exponential distribution.
This chart is also easier to be designed and implemented than other CUSUM charts for monitoring both T and X.
In this paper, we present the procedure to conduct the economic-statistical design of multivariate control charts for monitoring the process mean vector and covariance matrix simultaneously; i.e. to economically determine the optimum values of the three test parameters such that the statistical constraints (including the type I error probability and power) of the control chart can be satisfied.
Figure 8 depicts the X bar and R control charts for monitoring the machining process under consideration.
Therefore, developing control charts for monitoring the multivariate lognormal quality characteristics in a three-stage process could be considered as a future research.
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