EMPIRICAL MODELING OF THE BAKING FURNACE TO PREDICT BAKED ANODE PROPERTIES

A soft-sensor model developed from historical carbon plant data and multivariate statistical methods was proposed in past work to obtain quick predictions of individual anode properties right after baking for quality control purposes. It could only be used for anodes baked at the coldest and hottest positions within the furnace due to the core sampling method used at the partner plant and the way the data is collected. To complement the soft-sensor, this work proposes a strategy to account for the thermal history of anodes baked at any position. It is shown that combining categorical variables for pit and baking positions and routinely available firing equipment data is sufficient to predict the temperature history of anodes baked in different positions, which is typically not measured during normal operation. The model will be integrated to the soft-sensor in the future to account for the impact of baking position on anode properties.