Optimal replacement of systems subject to shocks and random threshold failure

Rangan, A.; Thyagarajan, Dimple; Sarada, Y.

doi:10.1108/02656710610704267

Cited by 7 publications

(5 citation statements)

References 15 publications

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“…t, A nÀ1 , (X n 4d \ Z n . g 1 )) = (G(g 2 ) + H(d, g 1 ) À H(d, g 2 )) nÀ1By similar arguments as above, we obtain the second term of the r.h.s of the equation(7).X k . t, A nÀ1 , (X n .…”

supporting

confidence: 55%

“…Many researchers studied the δ − shock model in the last 20 years or so. Lam and Zhang, 6 Rangan et al, 7 Li and Kong, 8 Li and Zhao, 9 Ma and Li, 10 Liang et al, 11 Eryilmaz and Bayramoglu, 12 Zhu et al, 13 Eryilmaz, 14,15 Tuncel and Eryilmaz, 16 Liu, 17 Ma et al, 18 Lorvand et al, 19 and Jiang 20 are among the researchers who investigated different aspects of δ − shock model. Models considering combination of above failure models for the systems are also proposed in the literature.…”

Section: Introductionmentioning

confidence: 99%

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On the reliability and optimal maintenance of systems under a generalized mixed δ-shock model

Bohlooli-Zefreh

Asadi

Parvardeh

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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This article is a study on the reliability characteristics of a system under a failure model called the generalized mixed [Formula: see text]-shock model. We assume that the system is subject to shocks according to a stochastic process. Each shock may cause some damage to the system. The system fails either the magnitude of the damage caused by a shock exceeds a threshold [Formula: see text] or the time between two consecutive shocks is less than a pre-specified threshold [Formula: see text] and simultaneously magnitude of the damage is bigger than a pre-specified critical threshold [Formula: see text] ([Formula: see text]). The survival function and other characteristics of the system lifetime are investigated. By imposing a cost function, we arrive at an optimal replacement policy for the system based on the proposed failure model. Several examples are provided under which we illustrate the theoretical results numerically and graphically.

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supporting

confidence: 55%

Section: Introductionmentioning

confidence: 99%

On the reliability and optimal maintenance of systems under a generalized mixed δ-shock model

Bohlooli-Zefreh

Asadi

Parvardeh

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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show abstract

Section: Introductionmentioning

confidence: 99%

“…In the subsequent years, research in this area was performed by Mallor and Santos (2003), Li and Pham (2005), Rangan et al (2006), Liu et al (2008) and Li et al (2010) where they presented a review and classification of shock models, developed a generalized model for evaluating the reliability of a multi-state degraded system, generalized a δ shock model by On cumulative damage threshold shock model 453 considering the threshold time to be a random variable and thereby opting for repair on system failure and analysed the reliability of degraded systems with multiple performance parameters subjected to random shocks, respectively.…”

Section: Introductionmentioning

confidence: 99%

System reliability computation and estimation based on a cumulative damage–threshold–shock model

Siju¹,

Kumar

2020

IJQRM

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PurposeThis article considers a reliability model where the failure is due to cumulative damage exceeding a threshold level. The concept that the threshold level of cumulative damage at each arrival of shock can change based on whether the magnitude of each shock exceeds its defined threshold level is considered to compute the system reliability.Design/methodology/approachThe stochastic process approach is used to obtain the cumulative damage based on Poisson arrival of shocks. The general expression for reliability is obtained using the conditional probability over each arrival of shock. The method of maximum likelihood estimation is used to obtain the estimators of the parameters and system reliability. A sensitivity analysis is performed to measure the effect of the parameter representing the rate of arrival of shock.FindingsThe maximum likelihood estimates of the reliability approach the actual reliability for increasing sample size. A sensitivity analysis study on the parameter representing the rate of arrival of shock shows that as the values of parameter increase (decrease), the reliability value decreases (increases).Originality/valueObtained a new expression for the cumulative damage–shock model and the findings are positively supported by presenting the general trend of estimated values of reliability approaching the actual value of reliability. The sensitivity analysis also genuinely supports our findings.

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“…Shock is an event that causes perturbation to the system, leading to its deterioration, the effect of these shocks on the system is measured by a process called the wear or damage process [11]. For instance, the wheel of an automobile receives shock while moving.…”

Section: Introductionmentioning

confidence: 99%

Reliability Evaluation under Shock Model

Ejembi¹,

Nggada²

2018

IJCA

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The approximation of reliability value for an engineering system is significant to predicting its possible successful operation. Typically, such approximation is done by taking into account system attributes and, or factors that may influence the operation of the system. An example of such attribute is calendar age while an example of a factor that could influence system operation is shock. This paper investigates the effect of shock on the reliability of a system component and then the system in its entirety. A general shock model is introduced from where the reliability model is developed with the assumption that components and system failure follows the exponential distribution. The developed model is then evaluated on example case studies.

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Optimal replacement of systems subject to shocks and random threshold failure

Cited by 7 publications

References 15 publications

On the reliability and optimal maintenance of systems under a generalized mixed δ-shock model

On the reliability and optimal maintenance of systems under a generalized mixed δ-shock model

System reliability computation and estimation based on a cumulative damage–threshold–shock model

Reliability Evaluation under Shock Model

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