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A predictive algorithm for estimating the quality of vehicle engine oil

Authors
Jun, H.-B.Conte, F.L.Kiritsis, D.Xirouchakis, P.
Issue Date
2008
Keywords
Degradation; Engine oil; Predictive maintenance; Statistical methods
Citation
International Journal of Industrial Engineering : Theory Applications and Practice, v.15, no.4, pp.386 - 396
Journal Title
International Journal of Industrial Engineering : Theory Applications and Practice
Volume
15
Number
4
Start Page
386
End Page
396
URI
https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/23475
ISSN
1072-4761
Abstract
Recently, with emerging technologies, visibility of vehicle information over the whole lifecycle becomes possible. The visibility opens up new challenging issues for improving the efficiency of vehicle operations. One of the most challenging problems arising during the middle of life (MOL) of vehicles is the predictive maintenance on engine oil. For this, in this study, we focus on developing a predictive algorithm to estimate the quality of the engine oil of a vehicle by analyzing its degradation status with mission profile data. For this purpose, we specify the relations between indicators of engine mission profiles and oil quality indicators using principal component analysis and regression method. Then, we develop a heuristic algorithm for estimating the value of a quality indicator of engine oil based on them. To evaluate the proposed approach, we carry out a case study and computational experiments. © International Journal of Industrial Engineering.
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