A knowledge-based real-time diagnostic system for PLC controlled manufacturing systems

This paper presents an approach to a knowledge-based real-time 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 developed in recent years. Diagnostic knowledge is acquired artificially and by model-based methods from the pneumatic and hydraulic circuit diagrams and the PLC program. The knowledge is the description of the functional and operational logic embedded in the PLC in a more usable form compared to that held in the mind of manufacturing system designers themselves. These models contain the design and engineering knowledge about the manufacturing system to be diagnosed. During the operation of the manufacturing system, the diagnostic system can continuously acquire data from the PLC, identify possible faults, search for their causes and suggest corrective actions.