A deep learning predictive model for selective maintenance optimization
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TLDR
In this paper, a predictive selective maintenance framework using deep learning and mathematical programming is developed to identify a subset of maintenance actions to perform on the components, and the objective is to minimize the total cost under intermission break time limitation.About:
This article is published in Reliability Engineering & System Safety.The article was published on 2022-03-01 and is currently open access. It has received 25 citations till now. The article focuses on the topics: Predictive maintenance & Component (thermodynamics).read more
Citations
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A two-stage stochastic programming model for selective maintenance optimization
TL;DR: In this article , a stochastic programming approach is proposed for determining an optimum maintenance plan to minimize maintenance costs and expected failure costs, while maximizing the probability of successful accomplishment of the next mission under uncertainties in future operating conditions.
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Application of structural topic modeling to aviation safety data
TL;DR: In this paper , structural topic modeling (STM) is applied to two text-based sets of aviation safety data, the Aviation Safety Reporting System (ASRS) and accident and incident reports published by the National Transportation Safety Board (NTSB).
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Multiple degradation-driven preventive maintenance policy for serial-parallel multi-station manufacturing systems
TL;DR: In this article , a multiple degradation-driven preventive maintenance (MDPM) policy for the serial-parallel multi-station manufacturing systems (SMMS) is proposed, where the degradation of the machine production rate (PR) is considered.
Journal ArticleDOI
Risk optimization using the Chernoff bound and stochastic gradient descent
André Gustavo Carlon,Henrique M. Kroetz,André Jacomel Torii,Rafael Holdorf Lopez,Leandro Fleck Fadel Miguel +4 more
TL;DR: In this paper , a stochastic gradient based method for the solution of risk optimization problems is proposed, which approximates the probability of failure evaluation by an expectation computation with the aid of the Chernoff bound.
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Recent advances and future trends on maintenance strategies and optimisation solution techniques for offshore sector
TL;DR: In this paper , the authors have carried out a review of recent state-of-the-art literature from which they have observed that the current state of the art does not incorporate site constraints of the asset related to offshore personnel resource availability and impact of time required to carry out activities, into the maintenance plan and its impact on other activities due to the maintenance.
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