A dynamic unreliability assessment and optimal maintenance strategies for multistate weighted <i>k</i>‐out‐of‐<i>n</i>:F systems

Khorshidi, Hadi Akbarzadeh; Gunawan, Indra; Ibrahim, Yousef

doi:10.1002/asmb.2173

Cited by 14 publications

(3 citation statements)

References 38 publications

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“…The power generation system reliability is determined based on estimated reliability values of each individual. Power generation gas engines are a k ‐out‐of‐ n system arrangement; thus, the equation for reliability of this arrangement is

R = \sum_{i = 0}^{k - 1} ((), \binom{n}{i}) {[R]}^{n - i} {[1 - R]}^{i} for asset in k - out - of - n .

…”

Section: Methodsmentioning

confidence: 99%

Reliability modelling with redundancy—A case study of power generation engines in a wastewater treatment plant

Jolfaei

Jin

Linden

et al. 2019

Quality & Reliability Eng

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Power generators are critical assets in wastewater treatment plants (WWTPs) in Australia and many countries. Better managing the lifetime, minimising failures, improving reliability and availability, and reducing operating and maintenance costs of the power generation assets are still challenging topics for water utilities. This case study aims to develop power generation system reliability and availability modelling considering redundancy to minimise operation and maintenance costs. The two‐parameter Weibull model was used to assess system reliability and availability to power generation engines in WWTPs. The Kaplan‐Meier method (a time‐driven estimation technique) and the log beta‐Weibull model (which is suitable for modelling censored and uncensored data) were used to analyse and validate the modelling results. Shape and scale parameters of the Weibull models were estimated by maximising the log‐likelihood function using non‐linear optimisation. Hazard and reliability functions were calculated using the Weibull model. Results using two‐parameter Weibull, Kaplan‐Meier, and log beta‐Weibull models display low reliability and high hazard rate over time, which was associated with spark plug failure due to a suboptimal start and stop operation strategy.

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R = \sum_{i = 0}^{k - 1} ((), \binom{n}{i}) {[R]}^{n - i} {[1 - R]}^{i} for asset in k - out - of - n .

…”

Section: Methodsmentioning

confidence: 99%

Reliability modelling with redundancy—A case study of power generation engines in a wastewater treatment plant

Jolfaei

Jin

Linden

et al. 2019

Quality & Reliability Eng

Self Cite

View full text Add to dashboard Cite

show abstract

“…They have assumed that the system is continuously monitored and the component failure can be known at any time. Khorshidi et al 99 considered a dynamic evaluation of a multi‐state weighted

k

‐out‐of‐

n

system. They used the expected failure cost of components as an unreliability index to compare the system unreliability and system cost for making decision.…”

Section: An Overview Of Classical Optimal Pm Modelsmentioning

confidence: 99%

An overview of some classical models and discussion of the signature‐based models of preventive maintenance

Asadi

Hashemi

2022

Appl Stoch Models Bus & Ind

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In reliability engineering literature, a large number of research papers on optimal preventive maintenance (PM) of technical systems (networks) have appeared based on preliminary many different approaches. According to the existing literature on PM strategies, the authors have considered two scenarios for the component failures of the system. The first scenario assumes that the components of the system fail due to aging, while the second scenario assumes the system fails according to the fatal shocks arriving at the system from external or internal sources. This article reviews different approaches on the optimal strategies proposed in the literature on the optimal maintenance of multi‐component coherent systems. The emphasis of the article is on PM models given in the literature whose optimization criteria (cost function and stationary availability) are developed by using the signature‐based (survival signature‐based) reliability of the system lifetime. The notions of signature and survival signature, defined for systems consisting of one type or multiple types of components, respectively, are powerful tools assessing the reliability and stochastic properties of coherent systems. After giving an overview of the research works on age‐based PM models of one‐unit systems and k‐out‐of‐n systems, we provide a more detailed review of recent results on the signature‐based and survival signature‐based PM models of complex systems. In order to illustrate the theoretical results on different proposed PM models, we examine two real examples of coherent systems both numerically and graphically.

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“…In our work, we focus on reliability assessment for load‐sharing systems that depend on component level data sets. The targets of system reliability assessment as an important reference for reliability system allocation and maintenance may vary in different situations. In this study, we consider the confidence limits of system reliability at a certain mission time as our assessment target.…”

Section: Introductionmentioning

confidence: 99%

Reliability assessment for load‐sharing systems with exponential components using statistical expansion as a correction

Xie

2019

Appl Stoch Models Bus & Ind

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Among recent system models, one specific type of system is generally used to model the dependence among components. Components are connected parallel in such systems as they fail one by one and are supposed to share the system work load. The model is thus referred to as the load‐sharing system model. Despite the availability of extensive reliability assessment methods for different systems, load‐sharing systems have not received enough attention from the scholars who have studied reliability assessment so far. Load‐sharing systems are generally designed for high levels of reliability. Therefore, tests for such systems can be expensive and time consuming. Limitation on resources always leads to small test sample sizes. This increases the difficulties associated with obtaining an accurate and robust system reliability assessment result. This paper proposes a novel assessment method for a certain type of load‐sharing system with components following exponential lifetime distributions. Based on the parameter estimation of the system reliability model, we introduce the Winterbottom‐Cornish‐Fisher asymptotic expansion method for implementing a correction of normal approximation. We demonstrate the accuracy of our method through a series of examples and simulation studies.

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A dynamic unreliability assessment and optimal maintenance strategies for multistate weighted k‐out‐of‐n:F systems

Cited by 14 publications

References 38 publications

Reliability modelling with redundancy—A case study of power generation engines in a wastewater treatment plant

Reliability modelling with redundancy—A case study of power generation engines in a wastewater treatment plant

An overview of some classical models and discussion of the signature‐based models of preventive maintenance

Reliability assessment for load‐sharing systems with exponential components using statistical expansion as a correction

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