In this paper we propose the explicit formulas of Average Run Length (ARL) of Exponentially Weighted Moving Average (EWMA) control chart for Autoregressive Integrated Moving Average: ARIMA (p,d,q) (P, D, Q)L process with exponential white noise. To check the accuracy, the ARL results were compared with numerical integral equations based on the Gauss-Legendre rule. There was an excellent agreeme...

The application of protective gel, which is a subprocess of the electronic assembly of the exhaust gas recircula‐ tion sensor, is a highly capable process with the fraction of nonconforming units as low as 200 ppm. Every unit is inspected immediately after gel application. The conven‐ tional Shewhart chart is of no use here, and the ap‐ proach based on the Bernoulli process is therefore conside...

The exponentially weighted moving average (EWMA) control chart has been widely studied as a tool for monitoring normal processes due to its simplicity and efficiency. However, relatively little attention has been paid to EWMA charts for monitoring Poisson processes. This paper extends EWMA charts to Poisson processes with emphasis on quick detection of increases in Poisson rate. Both cases with...

In many applications the shift directions of observation vectors are limited, which allows focusing detection power on a limited subspace with improved sensitivity. This paper develops a new multivariate nonparametric statistical process control chart for monitoring location parameters, which is based on integrating a directional multivariate spatial-sign test and exponentially weighted moving ...

Nonparametric (distribution-free) control charts have been introduced in recent years when quality characteristics do not follow a specific distribution. When the sample selection is prohibitively expensive, we prefer ranked-set sampling over simple random because ranked set sampling-based outperform charts. In this study, proposed nonparametric homogeneously weighted moving average based on Wi...

The EWMA chart for the standard deviation is a useful tool for monitoring the variability of a process quality characteristic. The performance of this chart is usually evaluated under the assumption of known parameters. However, in practice, process parameters are estimated from an in-control Phase I data set. A modified EWMA control chart is proposed for monitoring the standard deviation when ...

Control charts are used to identify the presence of assignable cause of variation in the process. Non-parametric control chart is an emerging area of recent development in the theory of SPC. Its main advantage is that it does not require any knowledge about the underlying distribution of the variable. In this paper a non-parametric control chart for controlling variability has been developed. I...

While the assumption of normality is required for the validity ofmost of the available control charts for jointmonitoring of unknown location and scale parameters, we propose and study a distribution-free Shewhart-type chart based on the Cucconi statistic, called the Shewhart-Cucconi (SC) chart. We also propose a follow-up diagnostic procedure useful to determine the type of shift the process m...