Please use this identifier to cite or link to this item: https://doi.org/10.1109/INDIN.2006.275766
Title: An intelligent predictive engine for milling machine prognostic monitoring
Authors: Li, X.
Zhou, J.
Zeng, H.
Wong, Y.S. 
Hong, G.S. 
Issue Date: 2007
Source: Li, X.,Zhou, J.,Zeng, H.,Wong, Y.S.,Hong, G.S. (2007). An intelligent predictive engine for milling machine prognostic monitoring. 2006 IEEE International Conference on Industrial Informatics, INDIN'06 : 1075-1080. ScholarBank@NUS Repository. https://doi.org/10.1109/INDIN.2006.275766
Abstract: This paper presents an intelligent predictive engine (IPE) for applications in equipment prognostic monitoring and failure prediction. The IPE is designed and developed with embedded data handling and analysis tools based on multiple regression models and artificial neural networks. A case study for milling machine tool remaining useful lifetime prediction is presented to demonstrate the usability of the IPE in tooling industry. A comparison is made in the case study on the prediction performances of the different models established with the same set of experimental data. Back propagation neural network shows clear better performance over the others for solving the prognostic problem of tool life prediction on the milling machine. The algorithms in the IPE are generic and can be adopted for different application scenarios that require equipment prognostic analysis. © 2006 IEEE.
Source Title: 2006 IEEE International Conference on Industrial Informatics, INDIN'06
URI: http://scholarbank.nus.edu.sg/handle/10635/73180
ISBN: 0780397010
DOI: 10.1109/INDIN.2006.275766
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