Monitoring of metallurgical plant performance with Bayesian change point detection algorithms

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Monitoring of metallurgical plant performance with Bayesian change point detection algorithms

Production data on mineral processing plants often show great variability, owing to measurement errors, changes in plant performance related to changes in ore characteristics or operating conditions, etc. This makes it difficult to assess plant performance where new equipment or reagents are being e...

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Bibliographic Details
Main Authors:	Aldrich, Chris, Paquet, U.
Other Authors:	Victor Babarovich
Format:	Conference Paper
Published:	Gecamin 2012
Online Access:	http://hdl.handle.net/20.500.11937/36033

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