Abstract :
As costs in equipment maintenance have been more and more expensive, equipment maintenance management is of great importance in equipment management in recent years. Firstly, cost of the equipment predictive maintenance model is proposed, which fully utilizes the big data technology. Particularly, the best maintenance cycle and maintenance times can be obtained exploiting the mutual game of the cost model based on the big data technology. Secondly, a novel equipment predictive maintenance method is proposed using general regression neural network, which is able to mine the relationship of data in a specific time series. Thirdly, four types of equipments are utilized in the experiment, including: 1)Dump truck, 2)Wheel loader, 3)Numerical control machine, and 4)Metal cutting machine. Experimental results demonstrate that our proposed general regression neural network based equipment predictive maintenance algorithm is able to predict maintenance cost accurately.
