The most well-known uni-arribute control chart used to monitor the number of nonconformities per unit is the Shewhart type C-chart. In this paper, a new method is proposed in an attempt to reduce the false alarm rate in the C-chart. To do this, the decision on beliefs (DOB) concept is first uti [1] Corresponding author e-mail: [email protected]   lized to design an iterative method, where...

This paper develops a new multivariate control charting method for vector autocorrelated and serially correlated processes. The main idea is to propose a Bayesian multivariate local level model, which is a generalization of the Shewhart-Deming model for autocorrelated processes, in order to provide the predictive error distribution of the process and then to apply a univariate modified EWMA con...

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...

Unlike a Shewhart chart, the exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) charts are memory control charts (also known as time weighted control charts) that are used for a quick detection of small shifts in the process mean. Control charts that combine information from present and past samples, like the EWMA and CUSUM charts have the ability to detect process changes ...

The accuracy of the measurement system is vital for reliable process monitoring using statistical control charts. applied chart’s effectiveness depends on system's performance. Measurement uncertainty can lead to incorrect decisions like unnecessary stops or failure intervene. In this paper, we investigated effect errors performance four well-established combined charts mean normally distribute...

A Cumulative Sum (CUSUM) control chart capable of detecting changes in both the mean and the standard deviation for autocorrelated data, referred to as the Max-CUSUM chart for Autocorrelated Process chart (MCAP chart), is proposed. This chart is based on fitting a time series model to the data, and then calculating the residuals. The observations are represented as a first-order autoregressive ...

The presence of asymmetric data in production processes or service operations has prompted the development new monitoring schemes. In this article, an adapted version exponentially weighted moving averages (EWMA) control chart with dynamic limits is proposed to monitor mean samples from skew-normal distribution. detection ability online was investigated by simulating average run length (ARL) pe...

Statistical process monitoring (SPM) literature recommends the combination of Shewhart and exponentially weighted moving average (EWMA) schemes to improve ability standalone EWMA in detecting small large shifts. The resulting scheme is named combined (or composite) Shewhart-EWMA (CSEWMA) scheme. In this paper, a new single composite (denoted as SCSEWMA) for mean when parameters are known or unk...

Industrial production requires multivariate control charts to enable monitoring of several components. Recently there has been an increased interest also in other areas such as detection of bioterrorism, spatial surveillance and transaction strategies in finance. In the literature, several types of multivariate counterparts to the univariate Shewhart, EWMA and CUSUM methods have been proposed. ...