Reliability analysis of a warm standby repairable system with two cases of imperfect switching mechanism

Sadeghi, Meisam; Roghanian, Emad

doi:10.24200/sci.2017.4063

Cited by 11 publications

(3 citation statements)

References 29 publications

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“…Li et al (2016) studied a warm standby repairable system in which the concept of vacation time in the repair facility was included. A Markovian system with a Laplace transform was considered by Sadeghi and Roghanian (2017) in the analysis of a warm standby repairable system that incorporated an imperfect switching mechanism. Zhai et al (2015) built a multi-valued decision diagram to analyse a demand-based warm standby system, in which each component had a nominal capacity and if the total capacity of the working components did not correspond to the system, it would fail.…”

Section: Introductionmentioning

confidence: 99%

A multi-state warm standby system with preventive maintenance, loss of units and an indeterminate multiple number of repairpersons

Castro

Dawabsha

2020

Computers & Industrial Engineering

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Section: Introductionmentioning

confidence: 99%

A multi-state warm standby system with preventive maintenance, loss of units and an indeterminate multiple number of repairpersons

Castro

Dawabsha

2020

Computers & Industrial Engineering

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“…Mokkadis et al [9] analysed a system by considering two types of repair and inspection of failed unit. Sadeghi and Roghanian [10] studied two unit warm standby system by considering two dissimilar units with imperfect . switching mechanism.…”

Section: Introductionmentioning

confidence: 99%

A Reliability Model for a Two Dissimilar Units Series System with Repair Time-Dependent Standby

Bhagwan

2020

IJEAT

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The present paper stochastically analyze a system comprising two dissimilar units (unit-1/unit-2) working in series configuration. System fails completely when either of the units gets failed. The repair time of unit-2 is considered to be much more as compared to the repair time of unit-1. So, to minimize the breakdown period of the system, a standby unit is provided against the second unit. Regenerative point technique (RPT) is used to develop a semi-markovian reliability model for the mentioned system. Optimum cut-off points concerning the profitability of the system have also been obtained. The model has applications in industries, particularly in aluminum industry.

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“…As per the literature survey, many types of research realized that Markovian modeling is widely used to analyze the performance indices of the repairable redundant system and to evaluate the reliability measures quantitatively. Many repairable redundant systems and performance indices of interest have been discussed using the theory of Markov process by several researchers (Lewis and Zhuguo, 1986; Ke et al , 2007; Sadeghi and Roghanian, 2017). Shekhar et al (2017a) analyzed a repairable machining framework with standby components for the study of the various reliability characteristics.…”

Section: Introductionmentioning

confidence: 99%

Transient analysis of computing system with reboot and recovery delay

Shekhar

Gupta

Jain

et al. 2020

IJQRM

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PurposeThe purpose of this paper is to present a sensitivity analysis of fault-tolerant redundant repairable computing systems with imperfect coverage, reboot and recovery process.Design/methodology/approachIn this investigation, the authors consider the computing system having a finite number of identical working units functioning simultaneously with the provision of standby units. Working and standby units are prone to random failure in nature and are administered by unreliable software, which is also likely to unpredictable failure. The redundant repairable computing system is modeled as a Markovian machine interference problem with exponentially distributed failure rates and service rates. To excerpt the failed unit from the computing system, the system either opts randomized reboot process or leads to recovery delay.FindingsTransient-state probabilities have been determined with which the authors develop various reliability measures, namely reliability/availability, mean time to failure, failure frequency, and so on, and queueing characteristics, namely expected number of failed units, the throughput of the system and so on, for the predictive purpose. To spectacle the practicability of the developed model, a numerical simulation, sensitivity analysis and so on for different parameters have also been done, and the results are summarized in the tables and graphs. The transient results are helpful to analyze the developing model of the system before having the stability of the system. The derived measures give direct insights into parametric decision-making.Social implicationsThe conclusion has been drawn, and future scope is remarked. The present research study would help system analyst and system designer to make a better choice/decision in order to have the economical design and strategy based on the desired mean time to failure, reliability/availability of the systems and other queueing characteristics.Originality/valueDifferent from previous investigations, this studied model provides a more accurate assessment of the computing system compared to uncertain environments based on sensitivity analysis.

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Reliability analysis of a warm standby repairable system with two cases of imperfect switching mechanism

Cited by 11 publications

References 29 publications

A multi-state warm standby system with preventive maintenance, loss of units and an indeterminate multiple number of repairpersons

A multi-state warm standby system with preventive maintenance, loss of units and an indeterminate multiple number of repairpersons

A Reliability Model for a Two Dissimilar Units Series System with Repair Time-Dependent Standby

Transient analysis of computing system with reboot and recovery delay

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