Development and economic evaluation of multivariate anodic incident detection systems.

• Individual anode current signals used to detect anode incidents in real-time. • Detection systems built with principal component analysis and an industrial dataset. • Best detection performance was achieved with the simplest system configuration. • Model profit metric developed to evaluate economic potential of detection systems. • Detection systems appear to be economically superior to standard detection method. Anodic incidents occur when an aluminum electrolysis cell short circuits at an anode position. They reduce the current efficiency of the affected cell, which makes it economically advantageous to detect and remove them as early as possible. This study evaluates the performance of three anodic incident detection systems of varying complexity. Individual anode current signals from 6 different cells were monitored with a Principal Component Analysis (PCA) model to detect anodic incidents using the Squared Prediction Error (SPE) statistic. The results suggest that a simple detection system using a common PCA model and a common detection threshold for all cells may be preferable. A novel approach to estimating the economic benefit of a detection system was also developed and used to optimize the systems' detection threshold. The anodic incident detection systems were found to deliver positive profits relative to the standard detection technique. [ABSTRACT FROM AUTHOR]