The purpose of this paper is to develop a new approach for equipment states prediction and provide a method for early warning of possible trouble states.
A new two-stage multi-level equipment state classification system was proposed to forecast equipment operation status. The first stage involves predicting the equipment's normal state, and the second stage involves forecasting the equipment's abnormal status. Meanwhile, the equipment state classification is done according to the manufacturing company's internal specifications to define various equipment statuses. Then, the trouble state and waiting state were predicted by grey state prediction model.
A new two-stage multi-level equipment status classification system and a new approach for equipment states prediction has been proposed in this paper.
The application on a real-world case shown that the model is very effective for predicting equipment state. The equipment's major failure risk can be reduced significantly.
The proposed approach can help improve the effective prediction of the equipment's various operation states and reduce the equipment's major failure risk and thus maintenance costs.
