Universiti Teknologi Malaysia Institutional Repository

Prediction of remaining useful life for mech equipment using regression

A. Bakir, A. and Zaman, M. and Hassan, A. and Hamid, M. F. A. (2019) Prediction of remaining useful life for mech equipment using regression. In: 8th International Conference on Mechanical and Manufacturing Engineering, ICME 2018, 16 July 2018 through 17 July 2018, Johor Bharu, Johor, Malaysia.


Official URL: http://dx.doi.org/10.1088/1742-6596/1150/1/012012


Maintenance has always been an important function in any manufacturing operations. Recently, Condition Based Maintenance (CBM) prognosis approach is gaining popularity in prediction of mechanical equipment remaining useful life (RUL). However, there is a need to improve the existing RUL prediction approach for mechanical equipment with multiple components. In this paper regression tree is used for developing the RUL prediction model of multiple components. A widely investigated dataset, PHM 2008 from NASA Prognostic Center was used in this study. Seven out of 21 sensors data were selected and used for prediction modeling. Before the data can be used, it must be filtered, clustered and normalized. Then the regression tree approach was used to develop the prediction model. The proposed regression tree model gave almost comparable results to other prediction methods such as Dempster-Shafer Regression (DSR), Support Vector machine (SVM) and Recurrent Neural Network (RNN). Besides, regression tree provides simplicity and the ability to manage large dataset.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:multiple components, prediction methods
Subjects:T Technology > TJ Mechanical engineering and machinery
Divisions:Mechanical Engineering
ID Code:89664
Deposited By: Yanti Mohd Shah
Deposited On:22 Feb 2021 14:08
Last Modified:22 Feb 2021 14:08

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