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Process monitoring and fault diagnosis have been studied widely in recent years, and the number of industrial applications with encouraging results has grown rapidly. In the case of complex processes a computer aided monitoring enhances operators' possibilities to run the process economically. In this paper a fault diagnosis system is described and some application results from the Outokumpu Harjavalta smelter are discussed. The system monitors process states using neural networks (Kohonen self-organizing maps, SOM) in conjunction with heuristic rules, which are also used to detect equipment malfunctions.