CCC-r chart extended approach of CCC charts, is a technique applied when nonconforming items are rarely observed. However, it is usually assumed that the inspection process is perfect in the implementation control charts imperfect inspections may have a significant impact on the performance of the control chart and setting the control limits. This paper first investigates the ...

Control chart is the most important Statistical Process Control tool used to monitor reliability and performance of industrial processes. For monitoring changes in process dispersion, the R and S charts are widely used. These control charts perform better under the ideal assumption of normality but are well known to be very inefficient in presence of outliers or departures from normality. In th...

(Correction made here after initial online publication.) Today's manufacturing environment has changed since the time when control chart methods were originally introduced. Sequentially observed data are much more common. Serial correlation can seriously affect the performance of the traditional control charts. In this article we derive explicit easy-to-use expressions of the variance of an EWM...

Traditionally, an ?̄? chart is used to control the process mean and an R chart is used to control the variance. However, these charts are not sensitive to the small shifts in the processes. The adaptive charts might be considered if the aim is to detect process changes quickly. In this paper, we propose a new adaptive single control chart which integrates the exponentially weighted moving averag...

In many manufacturing processes, the quality of a product is characterized by a non-linear relationship between a dependent variable and one or more independent variables. Using nonlinear regression for monitoring nonlinear profiles have been proposed in the literature of profile monitoring which is faced with two problems 1) the distribution of regression coefficients in small samples is unkno...

Process monitoring through control charts is a quite popular practice in statistical process control. From a statistical point of view, a superior control chart is the one which has an efficient design structure, for the case of both known and unknown parameters. There are auxiliary information–based location charts for an improved monitoring of process mean level. These charting structures hav...

Control charts have been widely recognized as important and critical tools in system monitoring for detection of abnormal behavior and quality improvement. In particular, multivariate control charts have been effectively used when a process involves a number of correlated process variables. Most existing multivariate control charts were developed using the assumption of normally distributed pro...

The control limits of an exponentially weighted moving average (EWMA) control chart should vary with time, approaching asymptotic limits as time increases. However, previous analytic analyses of EWMA charts consider only asymptotic control limits. In this article, the run length properties of EWMAs with time-varying control limits are approximated using nonhomogeneous Markov chains. Comparing t...

The control chart is an important statistical technique that is used to monitor the quality of a process. Shewhart control charts are used to detect larger disturbances in the process parameters, whereas CUSUM and EWMA charts are meant for smaller and moderate changes. Runs rules schemes are generally used to enhance the performance of Shewhart control charts. In this study, we propose two runs...