Dynamic reliability modeling for general standby systems

Alkaff, Abdullah; Qomarudin, Mochamad Nur; Purwantini, Elly; Wiratno, Stefanus Eko

doi:10.1016/j.cie.2021.107615

Cited by 20 publications

(6 citation statements)

References 35 publications

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“…Reliability of a technical object is commonly understood as the probability that the technical object, when used under specified conditions, will remain continuously in a state of operational condition until a given moment t [12,[31][32][33]. This can be described using the relation:…”

Section: Methodsmentioning

confidence: 99%

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Reliability Analysis of Military Vehicles Based on Censored Failures Data

2022

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The paper proposes a methodology of reliability testing as applied to vehicles used in military transport systems. After estimating the value of the reliability function using the Kaplan–Meier estimator, reliability models were developed and analysed. The neural model, which achieved the value of the correlation coefficient R exceeding 0.99, was determined to fit the empirical data the best. On the basis of the approximated reliability function of several models, the reliability characteristics of the tested sample of vehicles were determined. Plots of the failure probability density function for all three models had similar courses over a significant part of the function domain. A failure intensity function was also determined, which varied between models. For the exponential and Weibull model, the expected mileage between failures was calculated, which proved impossible for the neural model. The proposed methodology is capable of modelling reliability characteristics based on the observation of an assumed period of the exploitation process of the selected group of military vehicles.

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Section: Methodsmentioning

confidence: 99%

“…Research fields dealing with reliability problems are frequently addressed in the scientific literature [9][10][11][12]. In the article [13], a reliability assessment method was developed as a decision support in the selection of a vehicle fleet for a transport company.…”

Section: Introductionmentioning

confidence: 99%

Reliability Analysis of Military Vehicles Based on Censored Failures Data

2022

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“…Alkaff et al [29] extend the state-space model and introduce a deceleration factor for available waiting systems with multistate components. These components follow matrix-based phase-type (PH) distributions.…”

Section: Reliabilitymentioning

confidence: 99%

Automated phase-type distribution fitting via expectation maximization

Mialaret,

Pereira,

Sá Barreto

et al. 2024

J Reliable Intell Environ

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In numerous practical domains such as reliability and performance engineering, finance, healthcare, and supply chain management, a common and formidable challenge revolves around the accurate modeling of intricate time-based data and event durations. The inherent complexities inherent to real-world systems often render the effective application of conventional statistical distributions a formidable task. Phase-type (PH) distributions emerge as a remarkably adaptable class of distributions ideally suited for modeling scenarios like failure times or response times, thanks to their Markovian representation. These distributions find utility in both analytical and simulation-driven approaches for system evaluation, and they are frequently employed to approximate empirical datasets. This paper introduces an approach that leverages user-friendly tools, graphical adjustment features, and integration with existing tools to streamline the process of fitting PH distributions to empirical data. Simplifying this procedure empowers domain experts to more accurately model complex systems, resulting in enhanced decision-making, more efficient resource allocation, improved reliability assessments, and optimized system performance across an extensive spectrum of practical domains where the analysis of time-based data remains pivotal. Furthermore, this study presents a method for the automated determination of parameters within a fitted Hyper-Erlang distribution. This method utilizes the Bayesian Information Criterion (BIC) within a Bayesian optimization framework integrated into an Expectation-Maximization (EM) algorithm. Consequently, it enables the derivation of the probability density function (pdf) for a given dataset through a combination of Hyper-Erlang distributions. Subsequently, this pdf serves as a critical tool for the assessment of system performance.

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“…The reliability function R(t) determines the probability of an event, in which a technical object operated under assumed conditions remains continuously in a state of technical suitability from time 0 to time t [1,16,17,34]. The mathematical reliability function description is presented by the dependence (9): 𝑅(𝑡) = 𝑃(𝑇 ≥ 𝑡)for 𝑡 ≥ 0, (9) where T is the failure time of the technical object.…”

Section: 2reliability Modellingmentioning

confidence: 99%

Semi-Markov approach for reliability modelling of light utility vehicles

Oszczypała¹,

Ziółkowski²,

Małachowski³

2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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Vehicles are important elements of military transport systems. Semi-Markov processes, owing to the generic assumption form, are a useful tool for modelling the operation process of numerous technical objects and systems. The suggested approach is an extension of existing stochastic methods employed for a wide spectrum of technical objects; however, research on light utility vehicles complements the subject gap in the scientific literature. This research paper discusses a 3-state semi-Markov model implemented for the purposes of developing reliability analyses. Based on an empirical course of the operation process, model was validated in terms of determining the conditional probabilities of interstate transitions for an embedded Markov chain, as well as parameters of time distribution functions. The Laplace transform was used to determine the reliability function, failure probability density function, failure intensity, and expected time to failure. Readiness index values were calculated based on ergodic probabilities.

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Dynamic reliability modeling for general standby systems

Cited by 20 publications

References 35 publications

Reliability Analysis of Military Vehicles Based on Censored Failures Data

Reliability Analysis of Military Vehicles Based on Censored Failures Data

Automated phase-type distribution fitting via expectation maximization

Semi-Markov approach for reliability modelling of light utility vehicles

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