Reliability, MTTF and steady-state availability analysis of systems with exponential lifetimes

Çekyay, Bora; Özekıcı, Süleyman

doi:10.1016/j.apm.2014.05.029

Cited by 24 publications

(11 citation statements)

References 24 publications

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“…Çekyay and Özekici (2015) stated that "system reliability, mean time to failure, and steady-state availability, are functions of the component failure rates. The primary objective is providing explicit expressions for these performance measures and obtaining various characterizations on their mathematical structures" [18]. Corvaro et al (2017) stated that "the complex of RAM factors constitutes a strategic approach for integrating reliability, availability, and maintainability, by using methods, tools and engineering techniques (Mean Time to Failure, Equipment Down Time and System Availability values) to identify and quantify equipment and system failures that prevent the achievement of productive objectives" [19].…”

Section: Maintenance Reliability and Availabilitymentioning

confidence: 99%

Increasing the Reliability of an Electrical Power System in a Big European Hospital through the Petri Nets and Fuzzy Inference System Mamdani Modelling

et al. 2021

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The big hospitals’ electricity supply system’s reliability is discussed in this article through Petri nets and Fuzzy Inference System (FIS). To simulate and analyse an electric power system, the FIS Mamdani in MATLAB is implemented. The advantage of FIS is that it uses human experience to provide a faster solution than conventional techniques. The elements involved are the Main Electrical Power, the Generator sets, the Automatic Transfer Switches (ATS), and the Uninterrupted Power Supply (UPS), which are analysed to characterize the system behaviour. To evaluate the system and identified the lower reliability modules being proposed, a new reliable design model through the Petri Nets and Fuzzy Inference System approach. The resulting approach contributes to increasing the reliability of complex electrical systems, aiming to reduce their faults and increase their availability.

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Section: Maintenance Reliability and Availabilitymentioning

confidence: 99%

Increasing the Reliability of an Electrical Power System in a Big European Hospital through the Petri Nets and Fuzzy Inference System Mamdani Modelling

et al. 2021

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“…Ç ekyay and Ozekici [5] discuss issues related to mean time to failure and availability when the mission or environmental process is semi-Markovian. The reader is referred to Ç ekyay and Ozekici [8,9] for issues related to performance analysis and maintenance of such modulated reliability models. First consideration of modulation in software reliability applications is due toÖzekici and Soyer [21] who assume that the failures of the software depend on its operational profile, which is now the environmental process that represents the sequence of operations that the software performs.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Analysis of Doubly Stochastic Markov Processes in Reliability

Ay¹,

Soyer²,

Landon

et al. 2020

Prob. Eng. Inf. Sci.

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Markov processes play an important role in reliability analysis and particularly in modeling the stochastic evolution of survival/failure behavior of systems. The probability law of Markov processes is described by its generator or the transition rate matrix. In this paper, we suppose that the process is doubly stochastic in the sense that the generator is also stochastic. In our model, we suppose that the entries in the generator change with respect to the changing states of yet another Markov process. This process represents the random environment that the stochastic model operates in. In fact, we have a Markov modulated Markov process which can be modeled as a bivariate Markov process that can be analyzed probabilistically using Markovian analysis. In this setting, however, we are interested in Bayesian inference on model parameters. We present a computationally tractable approach using Gibbs sampling and demonstrate it by numerical illustrations. We also discuss cases that involve complete and partial data sets on both processes.

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“…They used a Monte Carlo simulation to analyze the correctness of their results. Çekyay and Özekici 7 tried to make the connection between k -out-of- n standby subsystems and exponentially distributed component lifetimes. They also analyzed MTFF and steady-state availability as a function of the component failure rates.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

A weighted K-means clustering approach to solve the redundancy allocation problem of systems having components with different failures

Karimi

Niaki

Miriha

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part O:

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A nonlinear integer programming model is developed in this article to solve redundancy allocation problems with multiple components having different failure rates in the series–parallel configuration using an active strategy. The main objective of this research is to select the number and the type of each component in subsystems so as the reliability of the system under certain constraints is maximized. To this aim, a weighted K-means clustering method is proposed, in which the analytical network process is employed to assign weights to the components of each cluster. As the proposed model belongs to the class of nondeterministic polynomial-time hardness problems, precise solution methods cannot solve it in large scale. Therefore, an invasive weed optimization algorithm, due to its proven high efficiency, is utilized to solve the problem. As there is no benchmark available in the literature, a harmony search algorithm and a genetic algorithm are employed as well to validate the results obtained. In order to find better solutions, response surface methodology is used to tune the parameters of the solution algorithms. Some numerical illustrations are solved in the end to not only show the application of the proposed methodology but also to validate the solution obtained and to compare the performance of the three solution algorithms. Experimental results are generally in favor of the invasive weed optimization.

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Reliability, MTTF and steady-state availability analysis of systems with exponential lifetimes

Cited by 24 publications

References 24 publications

Increasing the Reliability of an Electrical Power System in a Big European Hospital through the Petri Nets and Fuzzy Inference System Mamdani Modelling

Increasing the Reliability of an Electrical Power System in a Big European Hospital through the Petri Nets and Fuzzy Inference System Mamdani Modelling

Bayesian Analysis of Doubly Stochastic Markov Processes in Reliability

A weighted K-means clustering approach to solve the redundancy allocation problem of systems having components with different failures

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