Reliability Importance of Components in a Real-Time Computing System with Standby Redundancy Schemes

Abstract

Component importance analysis is to measure the effect on system reliability of component reliabilities, and is used to the system design from the reliability point of view. On the other hand, to guarantee high reliability of real-time computing systems, redundancy has been widely applied, which plays an important role in enhancing system reliability. One of commonly used type of redundancy is the standby redundancy. However, redundancy increases not only the complexity of a system but also the complexity of associated problems such as common-mode error. In this paper, we consider the component importance analysis of a real-time computing system with warm standby redundancy in the presence of Common-Cause Failures (CCFs). Although the CCFs are known as a risk factor of degradation of system reliability, it is difficult to evaluate the component importance measures in the presence of CCFs analytically. This paper introduces a Continuous-Time Markov Chain (CTMC) model for real-time computing system, and applies the CTMC-based component-wise sensitivity analysis which can evaluate the component importance measures without any structure function of system. In numerical experiments, we evaluate the effect of CCFs by the comparison of system performance measure and component importance in the case of system without CCF with those in the case of system with CCFs. Also, we compare the effect of CCFs on the system in warm and hot standby configurations.

Effectiveness Analysis of a Two Non-Identical Unit Standby System with Switching Device and Proviso of Rest

“…In continuity to earlier work, Chib et al (2014Chib et al ( , 2016 used the concept of proviso of rest in analyzing the system model and a two unit cold standby with partial and total failure and priority, Sharma et al (2012) analyzed stochastic behavior of a two-unit system with partial failure and fault detection. Further, Park (2014) carried out a warranty cost analysis for multi-component systems with imperfect repair and Zheng et al (2018) discussed the reliability importance of components with standby redundancy schemes in a real-time computing system. From the above literature, it is clear that all the models have the assumption that the repair facility is continuously available to attend to the repair of the failed unit.…”

A failure tracing method with hierarchical digraph and meta action for complex electromechanical systems

“…In this study, the failure influence degree of meta action will be considered from the following two angles: From the perspective of the influence of node failure probability on the system failure probability, the failure influence degrees of meta action can be depicted by their criticality importance 44,45 . Assume the system's failure probability function noted as $${F_s}(t)$$, and then the criticality importance (i.e., failure influence degree) of meta action A i can be calculated by: $$\begin{equation}I{D_{1i}}(t) = \frac{{{F_i}(t)}}{{{F_s}(t)}} \cdot \frac{{\partial {F_s}(t)}}{{\partial {F_i}(t)}}\end{equation}$$ where $$I{D_{1i}}(t)$$ is the failure influence degree of meta action A i under the first aspect, $${F_i}(t)$$ represents the failure probability function of the meta action A i .…”

Reliability assessment for multi-state automatic ticket vending machine (ATVM) through software and hardware failures

“…Sensitivity analysis was also performed to determine which machine affects the system reliability the most. Zheng et al (2018) performed the sensitivity analysis of a real-time computing system with one warm standby redundancy in the presence of the CCF (common cause failure) with the help of continuous-time Markov chain. The effect of the CCF in case of hot and warm standby redundancy was compared.…”