Two-stage multi-level equipment grey state prediction model and application
Grey Systems: Theory and Application
ISSN: 2043-9377
Article publication date: 15 October 2021
Issue publication date: 28 February 2022
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
A new two-stage multi-level equipment status classification system and a new approach for equipment states prediction has been proposed in this paper.
Practical implications
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.
Originality/value
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.
Keywords
Acknowledgements
This work was supported by a projects of the National Natural Science Foundation of China (72071111, 71671091). It is also supported by a joint project of both the NSFC and the RS of the UK (71811530338), a project of Intelligence Introduction base of the Ministry of Science and Technology (G20190010178). At the same time, the authors would like to acknowledge the partial support of the Fundamental Research Funds for the Central Universities of China (NC2019003).
Citation
Li, Q., Liu, S. and Javed, S.A. (2022), "Two-stage multi-level equipment grey state prediction model and application", Grey Systems: Theory and Application, Vol. 12 No. 2, pp. 462-482. https://doi.org/10.1108/GS-03-2021-0046
Publisher
:Emerald Publishing Limited
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