Cost-effective condition-based maintenance using markov decision processes

Amari, Suprasad V.; McLaughlin, Laura; Pham, Hoang

doi:10.1109/rams.2006.1677417

Cited by 55 publications

(30 citation statements)

References 3 publications

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“…The equipment is inspected and maintained periodically and the optimal inspection or maintenance frequency is calculated to obtain the minimal cost or the maximal availability. Similar results can also be found in many other areas [9][10][11]. In [12,13], the authors point out that the classical maintenance model may be inaccurate compared to the real world especially when the inspection rates are non-periodic, and a new Markov state diagram is proposed to solve the problem, the basic idea of which is to divide the original deterioration process into several sub deterioration processes.…”

Section: Introductionsupporting

confidence: 60%

Transient outage model considering corrective and preventive maintenance

Zhang

et al. 2016

J. Mod. Power Syst. Clean Energy

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Traditional outage model for the power equipment usually focus on the behavior of the equipment under random factors, and the availability of the power equipment in system analysis is usually confined to the steady value. However, this model may be inaccurate in the short term analysis, where the transient process of availability has not ended yet. Furthermore, the power equipment in the short term analysis might be influenced by both random factors and deterministic factors, yet the impact of deterministic factors cannot be completely reflected in the traditional outage model. Based on the above issues, a Markov-based transient outage model is proposed in this paper, which describes the deterioration and repair process of an equipment. Both the corrective maintenance and preventive maintenance are concerned in the model. The preventive maintenance in the model is considered as deterministic event, in which the start time and duration are both scheduled. Meanwhile the corrective maintenance and the unexpected failure are modeled as random events. The transient state probability and availability of equipment under preventive maintenance is derived. The effect of deterministic events on the availability of equipment is analyzed on numerical tests. The proposed model can be used in the short-term reliability assessment and maintenance scheduling in actual systems.

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Section: Introductionsupporting

confidence: 60%

Transient outage model considering corrective and preventive maintenance

Zhang

et al. 2016

J. Mod. Power Syst. Clean Energy

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“…However, investigations on United Airlines aircraft components, the U.S. Navy and various industries indicate that only about 15% to 20% of equipment failures are age-related. The other 80% to 85% of equipment failures are based totally on the effects of random events that happen in the system [3].…”

Section: Time Based Maintenance and Condition Basedmentioning

confidence: 99%

On-Line Residual Life Estimation with Outlier Judgement for Condition Based Maintenance

Goto

Tsukamoto

2011

Stochastic Systems Theory and its Applications (SSS)

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A method of on-line residual life prediction is proposed for condition based maintenance of industrial equipment. With on-line monitoring of condition of the industrial equipment, the residual life is evaluated by using on-line prediction of the equipment deterioration. The deterioration prediction is based on the on-line identification of the mathematical model of deterioration process. To improve the accuracy of the deterioration prediction, outlier elimination technique is introduced. The proposed method was applied to actual data of rotating equipment in a thermal power plant and the results verified the effectiveness of the proposed method.

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“…These periods of maintenance are scheduled with adequate planning. However, failures despite preventive maintenance would still occur [17] . Hence, there is a need to closely monitor the performance of the plants and also sense telltale signs of onset of failure, if any, and undertake preventive maintenance before a catastrophic failure could occur.…”

Section: Integrated Maintenance Of Lepsmentioning

confidence: 99%

A systemic approach to integrated E-maintenance of large engineering plants

Verma

Srividya

Ramesh

2010

Int. J. Autom. Comput.

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Large engineering plants (LEPs) have certain unique features that necessitate a maintenance strategy that is a combination of both time and condition based maintenance. Although this requirement is appreciated to varying degrees by asset owners, applied research leading to a systematic development of such a maintenance strategy is the need of the day. Such a strategy should also adopt a wholesome "systemic" approach so that the realization of the overall objectives of maintenance is maximized. E-maintenance has several potential benefits for large engineering plants. In this paper, a three pronged strategy is suggested for the successful implementation of e-maintenance for LEPs. Firstly, an integrated condition and time based maintenance framework is proposed for LEPs. Secondly, reference is drawn to models for condition and time based maintenance at systemic levels. As a part of the ab initio development of a condition monitoring system for a LEP, one of the characteristics of the condition monitoring system, namely, predictability, is discussed in detail as a sample for a systemic study. Thirdly, emphasis is laid on the information and expertise available in the domain of plant design, operation and maintenance and the same is tapped for incorporation in maintenance decision making.

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Cost-effective condition-based maintenance using markov decision processes

Cited by 55 publications

References 3 publications

Transient outage model considering corrective and preventive maintenance

Transient outage model considering corrective and preventive maintenance

On-Line Residual Life Estimation with Outlier Judgement for Condition Based Maintenance

A systemic approach to integrated E-maintenance of large engineering plants

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