On reducing false alarms in multivariate statistical process control
Chen, T (2010) On reducing false alarms in multivariate statistical process control Chemical Engineering Research and Design, 88 (4). 430 - 436. ISSN 0263-8762
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Official URL: http://dx.doi.org/10.1016/j.cherd.2009.09.003
The primary objective of this note is to reduce the falsealarms in multivariatestatisticalprocesscontrol (MSPC). The issue of falsealarms is inherent within MSPC as a result of the definition of control limits. It has been observed that under normal operating conditions, the occurrence of “out-of-control” data, i.e. falsealarms, conforms to a Bernoulli distribution. Therefore, this issue can be formally addressed by developing a Binomial distribution for the number of “out-of-control” data points within a given time window, and a second-level control limit can be established to reduce the falsealarms. This statistical approach is further extended to consider the combination of multiple control charts. The proposed methodology is demonstrated through its application to the monitoring of a benchmark simulated chemical process, and it is observed to effectively reduce the falsealarms whilst retaining the capability of detecting process faults.
|Additional Information:||NOTICE: this is the author’s version of a work that was accepted for publication in Chemical Engineering Research and Design. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Chemical Engineering Research and Design, 88(4), April 2010, DOI 10.1016/j.cherd.2009.09.003.|
|Divisions:||Faculty of Engineering and Physical Sciences > Chemical and Process Engineering|
|Deposited By:||Symplectic Elements|
|Deposited On:||11 Jun 2012 17:02|
|Last Modified:||25 Apr 2013 13:48|
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