Advisor
Merchant, William R.
Committee Member
Yu, Han
Committee Member
Larkins, Randy J.
Committee Member
Dzhamay, Anton
Department
College of Education and Behavioral Sciences, Department of Applied Statistics and Research Methods
Institution
University of Northern Colorado
Type of Resources
Text
Place of Publication
Greeley, (Colo.)
Publisher
University of Northern Colorado
Date Created
12-2021
Extent
872 pages
Digital Origin
Born digital
Abstract
Control charts are an important element for monitoring production processes in a wide array of industries. A strong performing control chart is one that responds quickly to undesirable changes in a production process. This work demonstrates the expansion of Multivariate Exponentially Weighted Moving Average and Covariance (MEWMAC) control chart to be doubly weighted in efforts to improve performance by reducing out of control run lengths (ARL1) when changes occur in either the process mean vector or covariance matrix. Metric derivation and justification are provided. Simulations under different scenarios provide comparison of the new control chart mechanism to those already established in the literature. Conclusions and recommendations for future research are discussed.
Degree type
PhD
Degree Name
Doctoral
Local Identifiers
Resch_unco_0161D_10975.pdf
Rights Statement
Copyright is held by the author.
