In this paper, two Shewhart-type nonparametric control charts based on runs rules are developed for monitoring the changes in the process variability. The charts are based on two nonparametric tests for equality of variances. The performance of the proposed control charts is evaluated for the normal, light tailed and heavy tailed distributions through average run length using simulations.

In this article, we introduce a method for monitoring the Weibull shape parameter β with type II (failure) censored data. The control limits depend on the sample size, the number of censored observations, the target average run length, and the stable value of β. The method assumes that the scale parameter α is constant during each sampling period, which is true under rational subgrouping. The p...

Not all data in practice came from a process with normal distribution. When the process distribution is non-normal or unknown, the commonly used Shewhart control charts are not suitable. In this paper, a new non-parametric CUSUM Mean Chart is proposed to monitor the possible small mean shifts in the process. The sampling properties of the new monitoring statistics are examined and the average r...

The combination of Shewhart control charts and an exponentially weighted moving average (EWMA) control charts to simultaneously monitor shifts in the mean output of a production process has proven very effective in handling both small and large shifts. To improve the sensitivity of the control chart to detect off-target processes, we propose a combined Shewhart-EWMA (CSEWMA) control chart for m...

It has recently been shown that the performance of multivariate exponentially weighted mean square (MEWMS) and multivariate exponentially weighted moving variance (MEWMV) charts of Huwang et al. (2007) in monitoring the variability of a multivariate process for individual observations is better than existing schemes. Both of these control charts monitor a distinct matrix which is an estimator o...

Abstract A single exponentially weighted moving average (EWMA) chart is effectively used for monitoring the process mean and variance simultaneously. In this paper, three single EWMA-type control charts including sum of square EWMA (SS-EWMA), maximum EWMA (MaxEWMA), and EWMA-semicircle (EWMA-SC) charts are compared under Lorenzen and Vance’s cost model integrating Taguchi’s loss function. The o...

Considering profiles as functional variables, two control charts are proposed for their monitoring in phase II. Due to its conformity with the nature of real-world profiles, applying functional model leads to proposed control charts obtained through functional data analysis techniques with desired features. These include simplicity in calculation and possibility of using them for different prof...