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...

multivariate control charts such as hotelling`s t^ 2 and x^ 2 are commonly used for monitoring several related quality characteristics. these control charts use correlation structure that exists between quality characteristics in an attempt to improve monitoring. the purpose of this article is to discuss some issues related to the g chart proposed by levinson et al. [9] for detecting shifts in ...

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 charts are graphical tools widely used to monitor manufacturing processes to quickly detect any change in a process that may result in a change in product quality. The statistic plotted on a control chart is based on samples of n ≥ 1 observations (rational subgroups) that may be taken at regular sampling intervals. However, there are numerous practical applications using individual obse...

Use of risk adjusted control charts for monitoring patients’ surgical outcomes is now popular.These charts are developed based on considering the patient’s pre-operation risks. Change point detection is a crucial problem in statistical process control (SPC).It helpsthe managers toanalyzeroot causes of out-of-control conditions more effectively. Since the control chart signals do not necessarily...

A few years ago, I was provided data on Hallsville ISD’s Texas Assessment of Academic Skills (TAAS) test results by Dr. Elizabeth Clark, Assistant Superintendent for Educational Operations. Elizabeth requested that I use statistical process control (SPC) charts to analyze the test scores and then submit recommendations for improvement. The reading and math charts are shown on Figures A and B, r...

Statistical process control (SPC) is a method of monitoring, controlling, and improving a process through statistical analysis. An important SPC tool is the control chart, which can be used to detect changes in production processes, including animal production systems, with a statistical level of confidence. This paper introduces the philosophy and types of control charts, design and performanc...

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...