Condition-based maintenance of naval propulsion systems: Data analysis with minimal feedback (original) (raw)
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A Prognostic Modeling Approach for Predicting Recurring Maintenance for Shipboard Propulsion Systems
Volume 1: Aircraft Engine; Marine; Turbomachinery; Microturbines and Small Turbomachinery, 2001
Accurate prognostic models and associated algorithms that are capable of predicting future component failure rates or performance degradation rates for shipboard propulsion systems are critical for optimizing the timing of recurring maintenance actions. As part of the Naval maintenance philosophy on Condition Based Maintenance (CBM), prognostic algorithms are being developed for gas turbine applications that utilize state-of-the-art probabilistic modeling and analysis technologies. Naval Surface Warfare Center, Carderock Division (NSWCCD) Code 9334 has continued interest in investigating methods for implementing CBM algorithms to modify gas turbine preventative maintenance in such areas as internal crank wash, fuel nozzles and lube oil filter replacement. This paper will discuss a prognostic modeling approach developed for the LM2500 and Allison 501-K17 gas turbines based on the combination of probabilistic analysis and fouling test results obtained from NSWCCD in Philadelphia. In t...
Reliability Engineering & System Safety
DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:
A condition-based maintenance policy for multi-component systems with a high maintenance setup cost
DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:
Closed-form analytical results for condition-based maintenance
Reliability Engineering & System Safety, 2002
Preventive maintenance is applied to improve the device availability or decrease the repair costs when the device failures are in deterioration (or aging) phase. Preventive maintenance can be made more ef®cient by periodic monitoring wherein the state of deterioration can be assessed. This leads to the notion of condition-based maintenance. In this paper, we study the condition-based maintenance, and derive closed-form expressions of system availability when the device undergoes both deterioration as well as Poisson type failures. These closedform solutions enable us to ®nd faster algorithms to determine the optimal inspection policy. q
Literature Review on Condition Based Maintenance Optimization
Condition Based Maintenance (CBM) can be termed as a maintenance strategy that monitors the particular condition of the system in order to choose what maintenance of the system must be done. CBM dictates that maintenance should solely be performed once the indicators show signs of decreasing performance or future failure. CBM relies on exploiting real-time information about the system to prioritize and optimize its maintenance resources. In general terms, condition monitoring is the observation of the state of the system. Such a framework can without much of a stretch confirm the equipment's well being, and act just if maintenance is genuinely required. Improvements as of late have permitted concentrated instrumentation of the framework, and in conjunction with better devices accessible for investigating the related information, the maintenance staff is ever ready now-a-days to select the best possible time for performing the maintenance of equipment. Ideally, condition based maintenance can enable the upkeep personnel to carry out only the right things at the right time, minimizing the spares cost, system downtime as well as the time required for maintenance. In the existing literature on condition based maintenance, attention has been paid to single as well as multi-component problems. For instance,
A Model-Based Approach for an Optimal Maintenance Strategy
PHM Society European Conference, 2014
In this paper we introduce a novel model-based reliability analysis methodology to guide the best maintenance practices for the different components in complex engineered systems. We have developed a tool that allows the system designer to explore the consequences of different design choices, and to assess the effects of faults and wear on critical components as a result of usage or age. The tool uses pre-computed simulations of usage scenarios for which performance metrics can be computed as functions of system configurations and faulty/worn components. These simulations make use of damage maps, which estimate component degradation as a function of usage or age. This allows the designer to determine the components and their respective fault modes that are critical w.r.t. the performance requirements of the design. Given a design configuration, the tool is capable of providing a ranked list of critical fault modes and their individual contributions to the likelihood of failing the different performance requirements. From this initial analysis it is possible to determine the components that have little to no effect on the probability of the system meeting its performance requirements. These components are likely candidates for reactive maintenance. Other component faults may affect the performance over the short or long run. Given a limit for allowable failure risk, it is possible to compute the Mean Time Between Failure (MTBF) for each of those fault modes. These time intervals, grouped by component or Line Replaceable Units (LRUs), are aggregated to develop a preventive maintenance schedule. The most critical faults may be candidates for Condition-Based Maintenance (CBM). For these cases, the specific fault Bhaskar Saha et. al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. modes considered for CBM also guide sensor selection and placement.
IEEE Transactions on Automation Science and Engineering, 2010
The importance of maintenance optimization has been recognized over the past decades and is highly emphasized by today's competitive economy. In this paper, an updated sequential predictive maintenance (USPM) policy is proposed to decide a real-time preventive maintenance (PM) schedule for a continuously monitored degrading system that will minimize maintenance cost rate (MCR) in the long term, by considering the effect of imperfect PM. The USPM model is continuously updated based on the change in the system state to decide an optimal PM schedule. Mathematical analysis of the proposed USPM model demonstrates the existence and uniqueness of an optimal PM schedule under practical conditions. The results validate that: 1) the proposed USPM model yields PM schedules that are consistent with the change in the system states and 2) the USPM model is able to quickly react to drastic degradation of the system and provide an optimal PM schedule in real time. The proposed maintenance policy can provide significant benefits for real-time maintenance decision making. Note to Practitioners-This paper is motivated by the gap that scheduling of commonly applied imperfect preventive maintenance (PM) (e.g., adding lubrication, partial replacement, etc.) scarcely considers a system's operating condition which is highly correlated with machine health and failures. The updated sequential predictive maintenance (USPM) policy developed in this paper outlines a framework for real-time PM scheduling in a cost-effective way. To implement the proposed method, it is necessary to: 1) monitor a performance variable (e.g., pressure, temperature, etc.) that well indicates the system state; 2) estimate the system lifetime distribution; 3) quantify the PM work orders; and 4) measure the maintenance cost. Although the proposed maintenance policy is based on the objective of minimizing maintenance cost rate (MCR), it can be easily revised according to other practical optimization objectives, i.e., maximizing system availability.
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2018
This article proposes a novel condition-based selective maintenance model for a multi-component system running multiple missions interspersed with scheduled intermission breaks. Each component in the system degrades according to a time-dependent stochastic process and fails whenever its degradation level reaches a prespecified threshold. Failures of system components are revealed only through periodic inspections performed during a mission. The decision to repair components found in a failed state is made at the beginning of the following break. However, a penalty cost proportional to the expected component downtime is incurred. To improve the probability of the system successfully completing its next mission, maintenance activities are carried out on its components during the breaks. Each component can be imperfectly maintained or replaced. The level at which maintenance is performed determines the improvement degree in the component health. Cost and time structures are developed t...