Multivariate control chats are generally used in situations where the simultaneous monitoring or control of two or more related quality characteristics is necessary. In most processes in the real world, distribution of the process characteristics are unknown or at least non-normal, so the non-parametric or distribution-free charts are desirable. Most non-parametric statistical process-control t...

Control charts are the most important tools of statistical process control used to discriminate between assignable and common causes of variation and to improve the quality of a process. To design a control chart, three parameters including sample size, sampling interval, and control limits should be determined. The objectives are hourly expected cost, in-control average run length, power of th...

• The Shewhart control charts, used for monitoring industrial processes, are the most popular tools in Statistical Process Control (SPC). They are usually developed under the assumption of independent and normally distributed data, an assumption rarely true in practice, and implemented with estimated control limits. But in general, we essentially want to control the process mean value and the p...

Conventional Phase II statistical process control (SPC) charts are designed using control limits; a chart gives a signal of process distributional shift when its charting statistic exceeds a properly chosen control limit. To do so, we only know whether a chart is out-of-control (OC) at a given time. It is therefore not informative enough about the likelihood of a potential distributional shift....

OBJECTIVE Applying statistical process control (SPC) charts in perinatal mortality surveillance (as an epidemiological indicator). METHOD The control charts were prepared using 51,840 births; 286 cases were produced from these births. All information came from SUSALUD between January 2004 and December 2007. Two control charts are presented; the first one's central line was considered to be th...

Control charts are one of the most important tools in statistical process control that lead to improve quality processes and ensure required quality levels. In traditional control charts, all data should be exactly known, whereas there are many quality characteristics that cannot be expressed in numerical scale, such as characteristics for appearance, softness, and color. Fuzzy sets theory is a...

In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the...

Background: The stock exchange, as a regulated financial market, in modern economies reflects their economic development level. The stock market indicates the mood of investors in the development of a country and is an important ingredient for growth. Objectives: This paper aims to introduce an additional statistical tool used to support the decision-making process in stock trading, and it inve...

Control of wellbore pressure during drilling operations has always been important in the oil industry as this can prevent the possibility of well blowout. The present research employs a combination of automatic process control and statistical process control for the first time for the identification, monitoring, and control of both random and special causes in drilling operations. To this end, ...