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The project Critical Process condition monitoring in recovery boilers, or CritMon, aim to further develop a model-based condition monitoring tool in order, among other things, to be able to see a critical temperature for the growth of deposits.

A problem encountered in process performance monitoring is that critical parameters cannot be measured due tounavailability of measurement techniques or difficult positioning. In model-based performance monitoring, suchproblems are overcome by combining existing measurements with a model to calculate the desired parameter.The application of this method for a process unit can reveal hidden trends in a large number of data.

This project will develop and validate models and methods for model-based performance monitoring of the criticaltemperature to avoid extensive fouling of recovery boiler surfaces. By monitoring the actual temperature vs. thecritical temperature at any condition it will be possible to operate closer to the critical point at controlled risk. Inthis way the average boiler efficiency and availability can be increased and the average operation can be closer tomaximum capacity. This increases CO2 neural power generation and pulp production at low marginal cost.