Equipment Maintenance Management And Fault Diagnosis For Tobacco Finished-product Logistics System

The improvement of extensive and out-dated equipment management and inefficient fault maintenance in tobacco automated logistics system has been carried out, relying on the equipment maintenance management and fault diagnosis for tobacco logistics system in Mianyang cigarette factory. This thesis presents an equipment maintenance management and fault diagnosis system for tobacco finished-product logistics system by combining advanced equipment maintenance management with intelligent fault diagnosis technology.Based on the structure of tobacco finished-product logistics system, a data acquisition system has been established by using OPC technology, and online real-time access to logistics equipment status information has been realized. Learning from the "six lean" equipment management mode advocated by tobacco industry, the project and process of equipment maintenance management have been optimized based on the existing methods of equipment management. An equipment maintenance management system has been developed to achieve the computerization and standardization of equipment maintenance management for tobacco finished-product logistics system. A fault diagnosis expert system has been developed by integrating the advantages of fault tree analysis and rule-based reasoning. In addition, this thesis proposes a conflict resolution strategy based on matching-degree and confidence to solve the matching-conflict problem present during system diagnostic reasoning. The algorithm of obtaining the minimal cut sets based on Petri nets is used as a fast solution to identify fault tree’s minimal cut sets involved in the proposed conflict resolution strategy. In order to improve the responsiveness to the breakdown, a remote fault alarm system has been designed based on GSM, and the management function of maintenance personnel on duty has been realized.An equipment maintenance management and fault diagnosis expert system has been realized based on C# and SQL Server database. The system not only meets the practical needs of the periodic or non periodic maintenance of logistics equipment, but also can accurately diagnose the various abnormal or fault condition in time and provide supplementary maintenance strategy based on the diagnosis results to improve the fault maintenance efficiency.