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Cuscore control charts for generalized feedback‐control systems
Author(s) -
Nembhard Harriet Black,
Chen Shuohui
Publication year - 2007
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.831
Subject(s) - autoregressive model , statistic , signal (programming language) , control chart , computer science , noise (video) , fault (geology) , autoregressive–moving average model , fault detection and isolation , statistical process control , control theory (sociology) , process (computing) , range (aeronautics) , moving average , statistics , control (management) , engineering , artificial intelligence , mathematics , aerospace engineering , seismology , actuator , image (mathematics) , programming language , geology , operating system
The cumulative score (Cuscore) statistic is devised to ‘resonate’ with deviations or signals of an expected type. When a process signal subject to feedback control occurs, it results in a fault signature in the output error. In this paper, Cuscore statistics are designed to monitor process parameters and characteristics measured by a generalized minimum variance (GMV) feedback‐control system sensitive to the fault signature of a spike, step, and bump signal. In this study, the GMV considered is a first‐order dynamic system with autoregressive moving average (ARMA) noise. We show theoretically that the performance of Cuscore charts is independent of the amount of variability transferred from the output quality characteristic to the adjustment actions in the GMV control system. Simulation is used to test the performance using the Cuscore charts. In general, the Cuscore can detect signals over a broad range of system parameter values. However, areas of low detection capability occur for certain fault signatures. In these cases, a tracking signal test is combined with the Cuscore statistics to improve detection performance. This study provides several illustrations of the underlying behavior and shows how the methodology developed can be easily applied in practice. Copyright © 2006 John Wiley & Sons, Ltd.