@inproceedings{bc5e4012d3514f1cae53625ebd02bb71,
title = "Post Prognostic Decision for Predictive Maintenance Planning with Remaining Useful Life Uncertainty",
abstract = "This paper investigates the use of the Particle Swarm Optimization (PSO) algorithm to quantify the effect of RUL uncertainty on predictive maintenance planning. The prediction of RUL is influenced by many sources of uncertainty, and it is required to quantify their combined impact by incorporating the RUL uncertainty in the optimization process to minimize the total maintenance cost. In this work, predictive maintenance of a multi-functional single machine problem is adopted to study the impact of RUL uncertainty on maintenance planning. Therefore, the PSO algorithm is integrated with a random sampling-based strategy to select a sequence that performs better for different values of RUL associated with different jobs. Through a numerical example, results show the importance of optimizing maintenance actions under the consideration of RUL randomness.",
keywords = "RUL, predictive maintenance, prog nostic post decision, scheduling",
author = "Khaled Benaggoune and Safa Meraghni and Jian Ma and Mouss, \{L. H.\} and Noureddine Zerhouni",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 Prognostics and Health Management Conference, PHM-Besancon 2020 ; Conference date: 04-05-2020 Through 07-05-2020",
year = "2020",
month = may,
doi = "10.1109/PHM-Besancon49106.2020.00039",
language = "英语",
series = "Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "194--199",
editor = "Jianyu Long and Zhiqiang Pu and Ping Ding",
booktitle = "Proceedings - 2020 Prognostics and Health Management Conference, PHM-Besancon 2020",
address = "美国",
}