Reliability Analysis of Repairable Systems With Dependent Component Failures Under Partially Perfect Repair

Yang, Qingyu; Zhang, Nailong; Hong, Yili

doi:10.1109/tr.2013.2259194

Cited by 54 publications

(7 citation statements)

References 32 publications

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“…and system design. [10][11][12] Hence, it is of natural interest to study active redundancy allocations policy when system components are statistically dependent. Gupta and Kumar 11 first investigated component versus system level active redundancy allocations policy with respect to some stochastic orders for matching spares when system components are statistically dependent but identically distributed (d.i.d.).…”

Section: Introductionmentioning

confidence: 99%

“…However in many practical scenarios components of a system may not be independent but are dependent because of various factors like different environmental factors (stress, load, voltage, etc.) and system design 10‐12 . Hence, it is of natural interest to study active redundancy allocations policy when system components are statistically dependent.…”

Section: Introductionmentioning

confidence: 99%

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Stochastic comparisons of coherent systems with active redundancy at the component or system levels and component lifetimes following the accelerated life model

Panja,

Kundu,

Pradhan

2023

Appl Stoch Models Bus & Ind

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An effective way to increase system reliability is to use redundancies (spares) into the systems either in component level or in system level. In this prospect, it is a significant issue that which set of available spares providing better system reliability in some stochastic sense. In this paper, we derive sufficient conditions under which a coherent system with a set of active redundancy at the component level or the system level provide better system reliability than that of the system with another set of redundancy, with respect some stochastic orders. We have derived the results for the component lifetimes following accelerated life (AL) model. The results obtained help us to design more reliable systems by allocating appropriate redundant components from the set of available options for the same. Various examples satisfying the sufficient conditions of the theoretical results are provided. Some results are illustrated with real‐world data.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stochastic comparisons of coherent systems with active redundancy at the component or system levels and component lifetimes following the accelerated life model

Panja,

Kundu,

Pradhan

2023

Appl Stoch Models Bus & Ind

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“…If some components of the system are deemed repairable, the system can be brought to its full operational capacity by replacing parts or by making adjustments [8]. In most works, the focus is on single-component repairable systems under various repair activities.…”

Section: Introductionmentioning

confidence: 99%

“…[226][227]. There may also be intermediate types of repairs (e.g., the partial perfect repair procedures mentioned in [8]). In the current work, the focus is on the case of minimal repair of the special type worse-than-old (WTO) [12].…”

Section: Introductionmentioning

confidence: 99%

Reliability Simulation of Two Component Warm-Standby System with Repair, Switching, and Back-Switching Failures under Three Aging Assumptions

et al. 2021

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We analyze the influence of repair on a two-component warm-standby system with switching and back-switching failures. The repair of the primary component follows a minimal process, i.e., it experiences full aging during the repair. The backup component operates only while the primary component is being repaired, but it can also fail in standby, in which case there will be no repair for the backup component (as there is no indication of the failure). Four types of system failures are investigated: both components fail to operate in a different order or one of two types of switching failures occur. The reliability behavior of the system is investigated under three different aging assumptions for the backup component during warm-standby: full aging, no aging, and partial aging. Four failure and repair distributions determine the reliability behavior of the system. We analyzed two cases—in the First Case, we utilized constant failure rate distributions. In the Second Case, we applied the more realistic time-dependent failure rates. We used three methods to identify the reliability characteristics of the system: analytical, numerical, and simulational. The analytical approach is limited and only viable for constant failure rate distributions i.e., the First Case. The numerical method integrates simultaneous Algebraic Differential Equations. It produces a solution in the First Case under any type of aging, and in the Second Case but only under the assumption of full aging in warm-standby. On the other hand, the developed simulation algorithms produce solutions for any set of distributions (i.e., the First Case and the Second Case) under any of the three aging assumptions for the backup component in standby. The simulation solution is quantitively verified by comparison with the other two methods, and qualitatively verified by comparing the solutions under the three aging assumptions. It is numerically proven that the full aging and no aging solutions could serve as bounds of the partial aging case even when the precise mechanism of partial aging is unknown.

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“…To model system reliability, most studies have considered partial of the system, hardware subsystem or software subsystem [1][2][3][4][5][6][7][8][9][10][11][12]. In the past few decades, a great number of reliability models in terms of hardware [1][2][3][4][5][6][7] and software [8][9][10][11][12] have been proposed in order to address hardware failures in hardware subsystems and software failures in software subsystems from various perspectives considering many critical applications, respectively. The interactions between hardware and software subsystems are often neglected for the sake of simplifying mathematical formulation, and hence, hardware and software subsystems are assumed as independent in most studies.…”

Section: Introductionmentioning

confidence: 99%

A Novel System Reliability Modeling of Hardware, Software, and Interactions of Hardware and Software

Zhu

Pham

2019

Mathematics

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In the past few decades, a great number of hardware and software reliability models have been proposed to address hardware failures in hardware subsystems and software failures in software subsystems, respectively. The interactions between hardware and software subsystems are often neglected in order to simplify reliability modeling, and hence, most existing reliability models assumed hardware subsystems and software subsystem are independent of each other. However, this may not be true in reality. In this study, system failures are classified into three categories, which are hardware failures, software failures, and hardware-software interaction failures. The main contribution of our research is that we further classify hardware-software interaction failures into two groups: software-induced hardware failures and hardware-induced software failures. A Markov-based unified system reliability modeling incorporating all three categories of system failures is developed in this research, which provides a novel and practical perspective to define system failures and further improve reliability prediction accuracy. Comparison of system reliability estimation between the reliability models with and without considering hardware-software interactions is elucidated in the numerical example. The impacts on system reliability prediction as the changes of transition parameters are also illustrated by the numerical examples.

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Reliability Analysis of Repairable Systems With Dependent Component Failures Under Partially Perfect Repair

Cited by 54 publications

References 32 publications

Stochastic comparisons of coherent systems with active redundancy at the component or system levels and component lifetimes following the accelerated life model

Stochastic comparisons of coherent systems with active redundancy at the component or system levels and component lifetimes following the accelerated life model

Reliability Simulation of Two Component Warm-Standby System with Repair, Switching, and Back-Switching Failures under Three Aging Assumptions

A Novel System Reliability Modeling of Hardware, Software, and Interactions of Hardware and Software

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