Optimum Preventive Maintenance Policy for a Mechanical System Using Semi-markov Method and Golden Section Technique

Kumar, Girish; Varghese, Joshua

doi:10.1109/ieem.2018.8607343

Cited by 8 publications

(3 citation statements)

References 6 publications

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“…В работе [18] для определения оптимального периода между восстановительными мероприятиями предложено использовать полумарковскую модель для неэкспоненциальных законов распределения наработки до отказа и времени восстановления, то есть методику можно применять для оборудования на этапе старения. Авторами осуществляется оптимизация по максимуму готовности системы, состоящей всего из двух элементов, то есть требуется доработка модели для ТОиР электрических сетей, являющихся многокомпонентными системами.…”

Section: плановое тоирunclassified

Electrical Network Maintenance: A Review

Gladkikh

2024

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Тюменский индустриальный университет, филиал в г. Нижневартовске, Нижневартовск, Россия Аннотация. Статья освещает вопросы, возникающие при организации технического обслуживания (ТО) и ремонта электрических сетей. В качестве основных видов ТО выделены корректирующее, плановое, основанное на оценке технического состояния, ориентированное на надежность и риск-ориентированное. Для каждой из стратегий (концепций) ТО выделены отличительные черты, достоинства и недостатки, определены факторы, обосновывающие целесообразность применения того или иного вида технического обслуживания при организации эксплуатации электрооборудования. Отмечены перспективы развития и противоречия, связанные с использованием той или иной концепции ТО. Рассмотрены некоторые модели оптимизации системы технического обслуживания и ремонта, учитывающие экономические, технические, технологические и другие факторы. Анализ исследований в области ТО и ремонта подтверждает необходимость моделирования процессов эксплуатации электрических сетей с целью их реализации в интеллектуальных цифровых инструментах. Обширность разработанных моделей доказывает тезис об отсутствии универсальной стратегии ТО и ремонта.

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Section: плановое тоирunclassified

Electrical Network Maintenance: A Review

Gladkikh

2024

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“…Thanks to the development of monitoring techniques providing the health condition of a component over time, condition-based maintenance (CBM) has become popular in industrial applications. Much literature has explored CBM in the last few years, focusing on the deterioration model of components (Kumar and Varghese, 2018; Endharta and Yun, 2017; Zhu et al , 2015). Applying CBM to multi-component systems with monitored data, such as oil analysis data, temperature data and vibration data, will also positively affect system reliability and maintenance efficiency (Jiang et al , 2019; Dutoit et al , 2019).…”

Section: Introductionmentioning

confidence: 99%

Condition-based opportunistic maintenance policy for a series–parallel hybrid system with economic dependence

Jiang

Huang

et al. 2021

JQME

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PurposeThe purpose of this paper is to propose a condition-based opportunistic maintenance policy considering economic dependence for a series–parallel hybrid system with a K-out-of-N redundant structure, where a single component in series is denoted as subsystem1, and K-out-of-N redundant structure is denoted as subsystem2.Design/methodology/approachBased on the theory of Residual Useful Life (RUL), inspection points are determined, and then different maintenance actions are adopted in the purpose of minimizing the cost rate. Both perfect and imperfect maintenance actions are carried out for subsystem1. More significantly, regarding economic dependence, condition-based opportunistic maintenance is designed for the series–parallel hybrid system: preemptive maintenance for subsystem1, and both preemptive and postponed maintenance for subsystem2.FindingsThe sensitivity analysis indicates that the proposed policy outperforms two classical maintenance policies, incurring the lowest total cost rate under the context of both heterogeneous and quasi-homogeneous K-out-of-N subsystems.Practical implicationsThis model can be applied in series–parallel systems with redundant structures that are widely used in power transmission systems in electric power plants, manufacturing systems in textile factories and sewerage systems. Considering inconvenience and high cost incurred in the inspection of hybrid systems, this model helps production managers better maintain these systems.Originality/valueIn maintenance literature, much attention has been received in repairing strategies on hybrid systems with economic dependence considering preemptive maintenance. Limited work has considered postponed maintenance. However, this paper uses both condition-based preemptive and postponed maintenance on the issue of economic dependence bringing opportunities for grouping maintenance activities for a series–parallel hybrid system.

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“…Adopting a risk-based T and M strategy is an essential step toward evaluating the effects of maintenance activities (MAs) on risk measures at both the component level and the system level. In this context, the question of quantifying the effects of maintenance strategies on risk measures has been discussed repeatedly in the literature (Vesely and Rezos, 1995;Baraldi et al, 2011;Kumar et al, 2012;Veeramany, 2012;Joel and Kumar, 2014;Zio and Compare, 2013;Kumar and Joel, 2018). In this regard, both the positive and the negative aspects of MAs should be quantified (Vesely and Rezos, 1995), thereby optimizing the MAs to reduce the risks or increase the availability of safety systems.…”

Section: Introductionmentioning

confidence: 99%

Multi-state Risk-Based Maintenance Analysis of Redundant Safety Systems Using the Markov Model and Fault Tree Method

Mohammadhasani

Pirouzmand

2021

Front. Energy Res.

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The risk-based maintenance strategy has received special attention in the safe operation of nuclear power plants. Simultaneous quantification of the positive and negative effects of maintenance activities and components degradation effect makes it possible to accurately evaluate the risk criterion for safety systems of nuclear power plants. However, it is difficult to integrate the effects of maintenance and components degradation into the standard reliability approaches. A straightforward approach for considering components degradation and different maintenance policies is to make use of Markov maintenance models. In this article, the effectiveness of maintenance activities (including changes in the surveillance test intervals and alteration in the different maintenance policies) on the components unavailability with considering aging effects is quantified using Markov maintenance models and then by coupling these models and the fault tree method, the risk measure is upgraded from the component level to the system level. The proposed models are applied to evaluate the unavailability of two safety systems of VVER-1000/V446 nuclear power plants as case studies. The results show that the Markov method due to its multi-state nature is effective in the conservative evaluation of risk measures so that the unavailability computed by the coupling process is higher than the original unavailability (calculated by system fault tree using PSA data of nuclear power plants) for all maintenance policies. In addition, this study illustrates that the developed Markov maintenance models could be applied to the large-scale whole plant level and provides a proper transition from the classical PSA methods to new techniques. This approach integrates the effects of maintenance strategies and components degradation. Also, it provides a practical and a more accurate tool to determine the technical specification of a real nuclear power plant from the risk point of view.

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Optimum Preventive Maintenance Policy for a Mechanical System Using Semi-markov Method and Golden Section Technique

Cited by 8 publications

References 6 publications

Electrical Network Maintenance: A Review

Electrical Network Maintenance: A Review

Condition-based opportunistic maintenance policy for a series–parallel hybrid system with economic dependence

Multi-state Risk-Based Maintenance Analysis of Redundant Safety Systems Using the Markov Model and Fault Tree Method

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