First Advisor
Merchant, William R.
Document Type
Dissertation
Date Created
12-2021
Department
College of Education and Behavioral Sciences, Applied Statistics and Research Methods, ASRM Student Work
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.
Extent
872 pages
Local Identifiers
Resch_unco_0161D_10975.pdf
Rights Statement
Copyright is held by the author.
Recommended Citation
Resch, Robert Eugene, "On the Development of the Self Starting Double Multivariate Exponentially Weighted Moving Average And Covariance Control Chart" (2021). Dissertations. 775.
https://digscholarship.unco.edu/dissertations/775