In the first part of this paper will be described an analysis of control problems and technical lifetime modeling of continuous casting device crystallizers. A full exploitation of continuous casting equipment (CCE) advantages can only be achieved through a control system that minimizes all undesirable effects on the technological process. Some of the undesirable effects influencing the CCE process effectiveness are the failures and service interruptions. This problem was solved by connection of dependability theory and artificial neural networks. The second part of the article refers to a model in linguistic form used to identify the type of defects present in the tested casting. This model, having the form of an attribute table, has been based on the concepts taken from the theory of rough sets and fuzzy logic. A methodology for construction of a heuristic model of linguistic knowledge was presented along with an example of its implementation based on the use of distributed sources of knowledge.
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