In many industrial manufacturing processes, the quality of products can depend on relative amount between two characteristics X and Y. Often, this calls for on-line monitoring ratio Z=X/Y as a characteristic itself by means control chart. A large number charts have been investigated in literature under assumption independent normal observations characteristics. practice, due to high frequency s...

Financial surveillance is an interesting area after financial crisis in recent years. In this subject, important financial indices are monitored using control charts. Control chart is a powerful instrument for detecting assignable causes which is considerably developed in industrial and service environments. In this paper, a monitoring procedure based on Shewhart control chart is proposed to mo...

Generally, the traditional Shewhart p chart has been developed by for charting the binomial data. This chart has been developed using the normal approximation with condition as low defect level and the small to moderate sample size. In real applications, however, are away from these assumptions due to skewness in the exact distribution. In this paper, a modified Exponentially Weighted Moving Av...

The quality characteristic(s) are assumed to follow the normal distribution in many control chart constructions, although this assumption may not hold some instances. This study proposes Bayesian-I and Bayesian-II Shewhart-type charts for monitoring Maxwell scale parameter phase II study. posterior predictive distributions used construct limits proposed charts, respectively. Various performance...

Control charts for monitoring of process variance are developed based on Shewhart, exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts for mean. In all these variance control charts, log transformation of the sample variance is used. The design procedure of this chart is complex and it is poorly understood by the industry. In this paper a EWMA chart for monito...

The classical Shewhart np-chart that constructed based on the binomial distribution is inappropriate in monitoring over-dispersion and correlated binary data where it tends to overestimate or underestimate the dispersion and subsequently lead to higher or lower false alarm rate in detecting out-of-control signals. Consequently, the np-chart is recommended based on a multiplicative-binomial dist...

BACKGROUND Comparison of outcomes requires adequate risk adjustment for differences in patient risk and the type of intervention performed. Both unintentional and intentional misclassification (also called gaming) of risk factors might lead to incorrect benchmark results. Therefore, misclassification of risk factors should be detected. We investigated the use of statistical process control tech...

The most commonly used statistical process control charts to detect special causes are Shewhart and Cusum charts. However, the Cuscore chart is a contemporary alternative that is especially well suited for detecting special causes that can be modeled in advance based on their characteristic effect on the system. In this paper, we develop the appropriate Cuscore statistic and the required contro...

When using control charts to monitor manufacturing processes, Shewhart control chart is known to be useful for detecting transient shifts, while the EWMA and CUSUM charts are useful for detecting persistent shifts. The efficiency of EWMA chart in monitoring location parameter can be improved by using an auxiliary variable that is closely related to the variable of interest. In this paper, an EW...