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In this study, Kappa number prediction and diagnosis in continuous Downflow Lo-Solids T M cooking application is investigated. Gustafson's Kappa number model is applied for the prediction of the blowline Kappa number. New cooking temperature set point is solved iteratively based on the difference between the predicted and target blow-line kappa numbers. The main active variables for the Kappa number are monitored using self-organizing map (SOM). The diagnosis and Kappa control are combined into a fault tolerant system. The data is collected from industrial continuous Downflow Lo-Solids T M cooking digester. Good results were achieved using the proposed approach.