This paper presents an approach to a novel and efficient diagnostic system for PLC controlled manufacturing systems. A general structure of the diagnostic system is implemented, which is the extension of an existing diagnostic system we have developed in recent years. We artificially get the diagnostic knowledge by model-based methods from the pneumatic and hydraulic circuit diagrams and the PLC program. Knowledge is embedded in the PLC as compared to more useful form, described in the manufacturing system designers keep their minds functionality and business logic. These models include the design and manufacturing systems engineering knowledge to make the diagnosis. Our proposed diagnostic system ca continuously acquire data from the PLC, identify possible faults, search for their causes and suggest corrective actions.
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