Time-varying failure rates in the availability and reliability analysis of repairable systems

Hassett, Thomas F.; Dietrich, D.L.; Szidarovszky, Ferenc

doi:10.1109/24.376543

Cited by 55 publications

(18 citation statements)

References 2 publications

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“…by making it into a nonhomogeneous Markov chain process. However, this kind of process has problems with the adjustment of the operating times and with tractability for some types of time-varying rates [8]. Even, if the limitations of the non-homogeneous Markov chain process were considered unimportant, this kind of modeling has another drawback that is discussed next.…”

Section: What Do the Assumptions Of Traditional Modeling Imply? 1)mentioning

confidence: 99%

A method for studying loss of component scenarios in a power system using stochastic point processes

Zapata

Torres²,

Kirschen

et al. 2009

2009 IEEE Power &Amp; Energy Society General Meeting

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This paper presents a method for studying the occurrence of loss of component scenarios in a power system using stochastic point process modeling. It can manage stationary and non stationary failure and repair rates, common mode failures of any order, components with any number of operating states and diverse repair logistics. The failure and repair sequences in each maintenance zone of the power system are generated using Monte Carlo simulation. A list of possible loss of component scenarios is therefore not required as in other methods. Loss of component scenarios are studied in terms of probability of occurrence, expected frequency and mean duration. By means of two examples, it is shown how the proposed method is a more flexible modeling tool than those based on Markov chains.Index Terms-Interconnected power systems, power system reliability, point processes, queuing analysis.

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Section: What Do the Assumptions Of Traditional Modeling Imply? 1)mentioning

confidence: 99%

A method for studying loss of component scenarios in a power system using stochastic point processes

Zapata

Torres²,

Kirschen

et al. 2009

2009 IEEE Power &Amp; Energy Society General Meeting

View full text Add to dashboard Cite

show abstract

“…This makes the mathematical analysis for systems with general lifetime distributions much more complicated. [9] studied a 1-out-of-2:G system with time-varying failure rates in a general polynomial expression format. Later, [13] presented an analytical model for components with various general lifetime distributions.…”

Section: Related Work On Modeling K-out-of-n:g Systemsmentioning

confidence: 99%

“…In the above models (e.g., [9,13]), every component in the system is assumed to conform to a single failure distribution and hence can only be applied to analyze systems with hot standby components. In manycore systems, as discussed earlier, an active embedded core in wait state should be treated as a warm standby component.…”

Section: Related Work On Modeling K-out-of-n:g Systemsmentioning

confidence: 99%

“…Recently, [25] presented an analytical model for k-out-of-(M + N):G repairable warm standby systems that consists of two different types of components. Most prior work (e.g., [16,9,13]) focuses on analyzing the lifetime reliability of gracefully degrading systems, in which all embedded cores are active. For standby redundant systems, an embedded core can be a "spare" unit, and such systems involve both warm standby (wait state) and cold standby (spare state) units as well as processing cores.…”

Section: Related Work On Modeling K-out-of-n:g Systemsmentioning

confidence: 99%

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On Modeling the Lifetime Reliability of Homogeneous Manycore Systems

Huang

2008

2008 14th IEEE Pacific Rim International Symposium on Dependable Computing

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Advancements in technology enable integration of a large number of cores on a single silicon die. At the same time, aggressive technology scaling has an ever-increasing adverse impact on the lifetime reliability of such large integrated circuits. In this work, we model the lifetime reliability of homogeneous manycore systems using a load-sharing nonrepairable k-out-of-n:G system with general failure distributions for embedded cores. In manycore systems, an embedded core can be in operational, cold standby, or warm standby state depending on system redundancy schemes and their workloads. We then use the proposed model to analyze the impact of different redundant schemes and configurations on the lifetime reliability of manycore systems.

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“…However, in practice, most of the electronic products exhibit time-varying failure rate during its lifetime, e.g., constantly decreasing failure rate, bathtub failure rate, roller-coaster failure rate, and zigzag failure rate curve have been found in various applications [8][9][10]. So in many situations, The Markov repairable model is not always available.…”

Section: Introductionmentioning

confidence: 99%

Instantaneous availability of a single-unit non-markov repair time omission

Yang

Wang

Zou

2009

2009 8th International Conference on Reliability, Maintainability and Safety

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This paper introduces a new model for a single-unit non-Markov repairable system in which the repair time is sufficiently short (less than some given critical value); it won't result in system failures. Such short repair interval can be omitted from the downtime record. In this paper the critical repair time is considered into two classes, one is a constant and the other is a non-negative random variable. Then the availability for the new model is calculated. Finally, some numerical examples are given to illustrate the proposed model.

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Time-varying failure rates in the availability and reliability analysis of repairable systems

Cited by 55 publications

References 2 publications

A method for studying loss of component scenarios in a power system using stochastic point processes

A method for studying loss of component scenarios in a power system using stochastic point processes

On Modeling the Lifetime Reliability of Homogeneous Manycore Systems

Instantaneous availability of a single-unit non-markov repair time omission

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