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- Title
A control scheme for monitoring process covariance matrices with more variables than observations.
- Authors
Li, Zhonghua; Tsung, Fugee
- Abstract
In this paper, we propose a new control chart that integrates a powerful high‐dimensional covariance matrix test with the exponentially weighted moving average procedure for monitoring high‐dimensional variability with individual observations. Design and implementation of the proposed chart are provided, including search algorithm and a table for the control limits, diagnostic aids after the signal, effect of misspecifying the in‐control distribution, and a bootstrap procedure. Monte Carlo simulation results show that the new chart, with its powerful inherited properties, provides satisfactory performance in various cases, especially for covariance shifts that involve diagonal components. The application of the proposed method is illustrated with a real data example from a white wine production process.
- Subjects
COVARIANCE matrices; QUALITY control; STATISTICAL process control; MOVING average process; SEARCH algorithms; STATISTICAL bootstrapping; MONTE Carlo method
- Publication
Quality & Reliability Engineering International, 2019, Vol 35, Issue 1, p351
- ISSN
0748-8017
- Publication type
Article
- DOI
10.1002/qre.2403