Design And Implementation Of Equipment Management Module Based On State Prediction

With the development of industrial production and the progress of science and technology, the level of modernization of equipment is increasing. Equipment plays the important role in the modernization of production. Equipment management receives attention and development. Condition monitoring and fault diagnosis are used to understand the status of equipment running and to troubleshoot the equipment. Modern production enterprises are maximizing the overall effectiveness. In most cases, the equipment is to be shut down, in accordance with the severity of failure, the trend, and the production circumstance. Therefore, in the event of equipment failure, Site personnel are most concern about the severity of failure and the trend. If we can confirm that the device can run for some time with trouble, it is possible to repair it at the most appropriate time.In this paper, the state prediction device is researched. The moving average, exponential smoothing, ARMA model and curve fitting approach are used to effectively monitor and forecast the status of the equipment. The recent trend and long-term forecast are used to forecast the status of the equipment. The examples indicates that forecast model reflects the basic trend of the time series the model error meets the engineering requirements.In this paper, the method of device management is researched. Condition Based Maintenance is an advanced way of maintenance, is the development direction. State Maintenance's main contents are condition monitoring, condition assessment and prediction, maintenance decisions and so on. The maintenance decision-making is researched. The maintenance decision-making factors are residual life of equipment, production situation, production and personal safety, spare parts and maintenance materials and so on.In this paper, state prediction is used to design the module of device management. The condition monitoring and fault diagnosis and the state prediction technology are used in the equipment management. We will get the effective implementation of predictive maintenance and improve the management level of modern equipment.