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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). pp. 430-436.

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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.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :
Chen, T
Date : 2010
DOI : 10.1016/j.cherd.2009.09.003
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.
Depositing User : Symplectic Elements
Date Deposited : 11 Jun 2012 16:02
Last Modified : 31 Oct 2017 14:36

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