Assessment of a multi-state system under a shock model

Eryılmaz, Serkan

doi:10.1016/j.amc.2015.06.129

Cited by 40 publications

(16 citation statements)

References 19 publications

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“…Besides, another important reliability characteristic is the mean residual lifetime function at a given time [3]. The reliability significance of this function is the average residual time until failure when the system is still working at time t. When compared with the average lifetime, this statistic is more flexible since it can be monitored throughout the working state.…”

Section: Reliability Characteristics Of the Systemmentioning

confidence: 99%

“…To sum up, a phase-type distribution has strong versatility to satisfy the requirements of modelling general phenomena. Eryilmaz [3], [4] introduced in detail the properties of a continuous phase-type distribution and its application. Following his approach, we assume that the inter-arrival time between shocks follows a continuous phase-type distribution.…”

Section: Introductionmentioning

confidence: 99%

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Reliability assessment of system under a generalized run shock model

2018

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In this paper we are concerned with modelling the reliability of a system subject to external shocks. In a run shock model, the system fails when a sequence of shocks above a threshold arrive in succession. Nevertheless, using a single threshold to measure the severity of a shock is too critical in real practice. To this end, we develop a generalized run shock model with two thresholds. We employ a phase-type distribution to model the damage size and the inter-arrival time of shocks, which is highly versatile and may be used to model many quantitative features of random phenomenon. Furthermore, we use the Markovian property to construct a multi-state system which degrades with the arrival of shocks. We also provide a numerical example to illustrate our results.

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Section: Reliability Characteristics Of the Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reliability assessment of system under a generalized run shock model

2018

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“…To integrate the random shock to reliability modeling for MSSs, Eryilmaz 11 considered a kind of multi‐state system subject to random shocks only. The multiple states are created by the various magnitudes of shocks.…”

Section: Introductionmentioning

confidence: 99%

Reliability analysis for multi‐state systems subject to distinct random shocks

Cao

Dong

2021

Quality & Reliability Eng

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This paper analyzes the competing and dependent failure processes for multi‐state systems suffering from four typical random shocks. Reliability analysis for discrete degradation is conducted by explicitly modeling the state transition characteristics. Semi‐Markov model is employed to explore how the system vulnerability and potential transition gap affect the state residence time. The failure dependence is specified as that random shocks can not only lead to different abrupt failures but also cause sudden changes on the state transition probabilities, making it easier for the system to stay at the degraded states. Reliability functions for all the exposed failure processes are presented based on the corresponding mechanisms. Interactions between different failure processes are also taken into account to evaluate the actual reliability levels in the context of degradation and distinct random shocks. An illustrative example of a multi‐state air conditioning system is studied to demonstrate how the proposed method can be applied to the engineering practice.

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“…A multistate k-out-of-n system and multi-state consecutive k-out-of-n system were respectively brought up in (Tian et al, 2008) and (Habib et al, 2007). Eryilmaz (2015) was proposed an extreme shock model considering that the system has been experienced several states before its complete failure. However, the abovementioned multi-state approaches all suffer from a significant constraint.…”

Section: Introductionmentioning

confidence: 99%

Reliability modeling and assessment of solder joints of electronic assemblies under mixed exposure to mechanical loads

Supriyono

Chen²,

Yapanto³

et al. 2021

SSMT

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Purpose In this paper, a lifetime estimation model for the solder joint is proposed which is capable of considering both severe and running mechanical shocks which is the real case in electric converters in the automotive and aerospace applications. This paper aims to asses the reliability of the solder joint under mixed exposure of mechanical loads. Design/methodology/approach Mechanical failure process may put at risk the perfect performance of any kinds of electronic systems regardless of the applications they are prepared for. Observation of solder joint health in an electronic assembly under simultaneous exposure of severe and running shocks is an open problem. Three commonly used soldering compositions are considered while the electronic assembly is exposed to three well-known driving cycles. Findings The results show that the best performance is achieved using SAC405 soldering alloy in comparison with Sn63Pb37 and SAC387 solder alloy. Consideration of mixed exposure to the mechanical loads leads to much more accurate lifetime estimation of the solder joint in the electronic assemblies. Originality/value The originality of the paper is confirmed.

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Assessment of a multi-state system under a shock model

Cited by 40 publications

References 19 publications

Reliability assessment of system under a generalized run shock model

Reliability assessment of system under a generalized run shock model

Reliability analysis for multi‐state systems subject to distinct random shocks

Reliability modeling and assessment of solder joints of electronic assemblies under mixed exposure to mechanical loads

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