Tuesday, August 9, 2011

Real Time Diagnostic System for PLC Controlled Manufacturing Systems

In sequence to meet the mission for flexibility and automation, a lot of complex systems of manufacturing are controlled by PLC (Programmable Logical Controller). This is since that PLC’s are flexible, modular, easy use and obtained at low cost. Nevertheless, their ability in fault diagnosis and detection is limited due to PLC’s inflexible programming system. Operation errors related with control of PLC processes frequently puzzle the personnel of maintenance at level workshop. Statistics illustrates that these errors happen most about 70% between all kinds of errors, and when such an error happens, about 80% of downtime is wasted locating its basis and only 20% is spent on the repair. The automated manufacturing systems availability and productivity can be enhanced by reduction their downtime resulted from errors. This has guided to the automatic diagnostic tools or systems development.

Generally when an error happens, personnel of maintenance will verify the PLC I/O at first. Then they will try to utilize a debugging tool of PLC software to trace the signals in the PLC with the PLC source code help, the machine design documentation and the inspections, until the signals of input, which have caused the error, are found. Nevertheless, this diagnosis process has been initiated with below bottlenecks:
• The programming devices of PLC do not support the logic circuits automatic analysis, which could assist in finding the most causes of the error.
• Most the code of PLC is presented graphically by ladder logic or function block diagrams. It is hard to interpret and complex programs functionality is difficult to recover.
• There is a giant documentation amount on the electrical, mechanical, and a complex system operative design. Mostly are required in order to resolve a problem.
• The personnel maintenance observation of the system manufacturing may be incorrect or incomplete, which may lead to wrong diagnosis.

Thus, intelligent system and automatic algorithms advances need to be examined to improve the diagnosing complex PLC efficiency controlled the systems of manufacturing. This is a part which is magnetizing more and more industrial partners and researchers. The goal of the advance was to create the manufacturing events sequence that happen for every station in the assembly line. Meaningful comparisons were completed between the state of simulated the system and the state of observed the system during the simulation. The tool was stimulated by observations concerning the current PLC software debugging tools inefficiency and the poor accessibility of cross-referenced manuals and documentation. The temporal signal prototype analyses reliance within the PLC logic model and a history of logged values. Matthias presented a method to model event based systems and illustrated how diagnosis of post-mortem depends on the use of such models can be executed for equipment of PLC controlled.

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