Background: The utility of statistical process control (SPC) methods has received growing interest in the healthcare community to help improve clinical and administrative processes. SPC charts are chronological graphs of process data that are used in many other industries to help understand, control, and improve processes and that, although based in statistical theory, are easy for practitioner...

Most of the inventory control models assume that quality defect never happens, which means production process is perfect. However, in real manufacturing processes, the production process starts its operation in the in-control state; but after a period of time, shifts to the out-of-control state because of occurrence of some disturbances. In this paper, in order to approach the model to real man...

Originally developed at Bell Laboratories by Dr Walter Shewhart [1] in 1924 specifically to help detect statistical changes in process quality, control charts have since become one of several primary tools of quality control and process improvement. Quality control charts are chronological graphs of process data that, although based in statistical theory, are easy for practitioners to use and i...

Time series control charts are popular methods for statistical process control of autocorrelated processes. In order to implement these methods, however, a time series model of the process is required. Since time series models must always be estimated from process data, model estimation errors are unavoidable. In the presence of modeling errors, time series control charts that are designed unde...

Control limits in traditional Multivariate Quality Control Charts (MQCC), such as Hotelling's T control chart, Multivariate Cumulative Sum (MCUSUM) and Multivariate Exponentially-Weighted Moving Average (MEWMA) control charts are based on multivariate normal assumption. This assumption is not usually satisfied, especially in real life applications. The purpose of a control chart based on suppor...

Control chart is the most important Statistical Process Control (SPC) tool used to monitor reliability and performance of manufacturing processes. Variability EWMA charts are widely used for the detection of small shifts in process dispersion. For ease in computation all the variability EWMA charts proposed so far are based on asymptotic nature of control limits. It has been shown in this study...

Processes characterized by high dimensional and mixture data challenge traditional statistical process control charts. In this study, we propose a multivariate control chart based on the Gower distance that can handle a mixture of continuous and categorical data. An extensive simulation study was conducted to examine the properties of the proposed control chart under various scenarios and compa...