Variable Sampling Rate Control Charts for Monitoring Process Variance

• Main Author: Hughes, Christopher Scott
• Other Authors: Statistics
• Format: Others
• Published: Virginia Tech 2014
• Subjects: Shewhart chart; integral equation; Markov chain; CUSUM chart; EWMA chart
• Online Access: http://hdl.handle.net/10919/37643; http://scholar.lib.vt.edu/theses/available/etd-041999-130738/

Industrial processes are subject to changes that can adversely affect product quality. A change in the process that increases the variability of the output of the process causes the output to be less uniform and increases the probability that individual items will not meet specifications. Statistical control charts for monitoring process variance can be used to detect an increase in the variability of the output of a process so that the situation can be repaired and product uniformity restored. Control charts that increase the sampling rate when there is evidence the variance has changed gather information more quickly and detect changes in the variance more quickly (on average) than fixed sampling rate procedures. Several variable sampling rate procedures for detecting increases in the process variance will be developed and compared with fixed sampling rate methods. A control chart for the variance is usually used with a separate control chart for the mean so that changes in the average level of the process and the variability of the process can both be detected. A simple method for applying variable sampling rate techniques to dual monitoring of mean and variance will be developed. This control chart procedure increases the sampling rate when there is evidence the mean or variance has changed so that changes in either parameter that will negatively impact product quality will be detected quickly. === Ph. D.