Control charts are extensively used in processes and are very helpful in determining the special cause variations so that a timely action may be taken to eliminate them. One of the charting procedures is the Shewhart-type control charts, which are used mainly to detect large shifts. Two alternatives to the Shewhart-type control charts are the cumulative (CUSUM) control charts and the exponentia...

Control charts have been broadly used for monitoring the process mean and dispersion. Cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are memory control charts as they utilize the past information in setting up the control structure. This makes CUSUM and EWMA-type charts good at detecting small disturbances in the process. This article proposes two new mem...

An approach is presented for conducting multiscale statistical process control (MSSPC), based on a library of basis functions provided by wavelet packets. The proposed approach explores the improved ability of wavelet packets in extracting features with arbitrary locations, and having different localizations in the time-frequency domain, in order to improve the detection performances achieved w...

This paper proposes two alternative schemes for the online recognition of control chart patterns (CCPs), namely: 1 a scheme based on direct continuous recognition 2 a scheme based on ‘recognition only when necessary’. The study focuses on recognition of six CCPs plotted on the Shewhart X-bar chart, namely, random, shift-up, shift down, trend-up, trend-down and cyclic. The artificial neural netw...

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...

Usually, in monitoring a proportion p < /em>, the binary observations are considered independent; however, in many real cases, there is a continuous stream of autocorrelated binary observations in which a two-state Markov chain model is applied with first-order dependence. On the other hand, the Bernoulli CUSUM control chart which is not robust to autocorrelation can be applied two-sided co...

The special causes of variations, which is also known as a shift, can occur in single or more than one related process characteristics. Statistical control tools such charts are useful to monitor shifts the parameters (location and/or dispersion). In real-life situation, shift emerging different sizes, and it hard identify with classical charts. Moreover, characteristics required attention beca...

RU4LEtWH&!4sl-A'ERG RU4LEtWH&!4sl Fig. 1. Fig. 1. Entropy per cell as function of average run length. Entropy per cell as function of average run length. distributed: for tl 2 0 for tl < 0 where t, is the (continuous) run length. The average run length is f, = 6. (20) Now, suppose the continuous run length tl is quantized to obtain the discrete run length t : t = [t1] + 1 (21) where [tl] = larg...

Background and objectives: Risk-adjusted Bernoulli control chart is one of the main tools for monitoring multistage healthcare processes to achieve higher performance and effectiveness in healthcare settings. Using parameter estimates can lead to significantly deteriorate chart performance. However, so far, the effect of estimation error on this chart in which healthcare ...