Monitoring of Proportional-Integral Controlled Processes using a Bayesian Time Series Analysis Method
Recently, there has been interest in applying statistical process monitoring methods to processes controlled with feedback controllers in order to eliminate assignable causes and achieve reduced overall variability. In this paper, we propose a Bayesian change‐point method to monitor processes regula...
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| Veröffentlicht in: | Quality and reliability engineering international 2014-12, Vol.30 (8), p.1341-1351 |
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| creator | Vanli, O. Arda |
| description | Recently, there has been interest in applying statistical process monitoring methods to processes controlled with feedback controllers in order to eliminate assignable causes and achieve reduced overall variability. In this paper, we propose a Bayesian change‐point method to monitor processes regulated with proportional‐integral controllers. The approach is based on fitting an exponential rise model to the control input actions in response to a step shift and employs a change‐point method to detect the change. Simulation studies show that the proposed method has better run‐length performance in detecting step shifts in controlled processes than Shewhart chart on individuals and special‐cause chart on residuals of time series model. Copyright © 2013 John Wiley & Sons, Ltd. |
| doi_str_mv | 10.1002/qre.1555 |
| format | Article |
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| issn | 0748-8017 1099-1638 |
| language | eng |
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| source | Wiley Journals |
| subjects | Bayesian analysis Computer simulation Control systems Controllers feedback control Monitoring Monitors Time series Time series analysis time series modeling |
| title | Monitoring of Proportional-Integral Controlled Processes using a Bayesian Time Series Analysis Method |
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