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...

This article is the first in a two-part series discussing and illustrating the application of statistical process control (SPC) to processes often examined by hospital epidemiologists. The basic philosophical and theoretical foundations of statistical quality control and their relation to epidemiology are emphasized in order to expand mutual understanding and cross-fertilization between these t...

Statistical Process Control (SPC) aims at quality improvements through reduction of variances. The best known tool of SPC is the control chart. Over the years the control chart has proved to be a successful practical technique for monitoring process measurements. However, its usefulness in practice is limited to those situations where it can be assumed that successive measurements are independe...

• Objective: To apply statistical process control (SPC) techniques to evaluate 3 components of the phacoemulsification cataract surgery procedure. • Design: Retrospective chart review. • Methods: We analyzed 180 cataract surgeries performed by 6 cataract surgeons (3 “high-volume” and 3 “low-volume” surgeons). Surgical parameters evaluated were phacoemulsification time (seconds), phacoemulsifica...

When a manufacturing process is subject to random shocks, detecting the changes in the process and adjusting an out-of-target process are two essential functions of process quality control. Traditional SPC techniques emphasize process change detection, but do not provide an explicit process adjustment method. This paper discusses a general sequential adjustment procedure based on Stochastic App...

in statistical quality control a very widely used measure is average run length (arl) which may be worked out by different methods like integral equation, approximations, and monte carlo simulations. the arl measure and the other related measures are of major significance in every type of production process. an omission in its computation (and hence its related measures such as extra quadratic ...

Statistical process control (SPC) charts are commonly used to monitor quality characteristics in manufacturing processes. When monitoring two or more related simultaneously, multivariate T2 often employed. Like univariate charts, chart pattern recognition (CCPR) plays a crucial role SPC. The presence of non-random patterns indicates that is influenced by one assignable causes and corrective act...

Statistical process control (SPC) has been used to achieve and maintain control of various processes in industry (Stoumbos, Reynolds, Ryan, and Woodall 2000). The control chart is a primary SPC tool to monitor process variability and promote quality improvement by means of detecting process shifts requiring corrective actions. As a graphical monitor, control charts generally contain a centerlin...

Statistical Process Control (SPC) charts are widely used in manufacturing industry for monitoring the performance of sequential production processes over time. A common practice using a control chart is to first collect samples and take measurements certain quality variables from them at equally-spaced sampling times, then make decisions about process status by based on observed data. In some a...