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.

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