Academic literature on the topic 'Imperfect Fault Coverage, Irrelevance Coverage Model, Reliability'

Purpose The internet of things and just-in-time are the embryonic model of innovation for the state-of-the-art design of the service system. This paper aims to develop a fault-tolerant machining system with active and standby redundancy. The availability of the fault-tolerant redundant repairable system is a key concern in the successful deployment of the service system. Design/methodology/approach In this paper, the authors cogitate a fault-tolerant redundant repairable system of finite working units along with warm standby unit provisioning. Working unit and standby unit are susceptible to random failures, which interrupt the quality-of-service. The system is also prone to common cause failure, which tends its catastrophe. The instantaneous repair of failed unit guarantees the increase in the availability of the unit/system. The time-to-repair by the single service facility for the failed unit follows the arbitrary distribution. For increasing the practicability of the studied model, the authors have also incorporated real-time machining practices such as imperfect coverage of the failure of units, switching failure of standby unit, common cause failure, reboot delay, switch over delay, etc. Findings For deriving the explicit expression for steady-state probabilities of the system, the authors use a supplementary variable technique for which the only required input is the Laplace–Stieltjes transform (LST) of the repair time distribution. Research limitations/implications For complex and multi-parameters distribution of repair time, derivation of performance measures is not possible. The authors prefer numerical simulation because of its importance in the application for real-time uses. Practical implications The stepwise recursive procedure, illustrative examples, and numerical results have been presented for the diverse category of repair time distribution: exponential (M), n-stage Erlang (Ern), deterministic (D), uniform (U(a,b)), n-stage generalized Erlang (GE[n]) and hyperexponential (HE[n]). Social implications Concluding remarks and future scopes have also been included. The studied fault-tolerant redundant repairable system is suitable for reliability analysis of a computer system, communication system, manufacturing system, software reliability, service system, etc. Originality/value As per the survey in literature, no previous published paper is presented with so wide range of repair time distribution in the machine repair problem. This paper is valuable for system design for reliability analysis of the fault-tolerant redundant repairable.

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.

In systems with Imperfect Fault Coverage (IFC), all components are subject to uncovered failures, possibly threatening the whole system. Therefore, to improve the system reliability, it is important to timely detect, identify, and shut down the components that are no more relevant for the system operation. Thus, the Irrelevance Coverage Model (ICM) was proposed based on the Imperfect Fault Coverage Model (IFCM). In the ICM, any component detected as irrelevant can be safely shut down without reducing the system reliability and preventing the case where its eventual failure may remain uncovered and cause a direct system failure. This not only improves the system reliability but also saves energy. This thesis solves the problem of quantitative evaluation of component relevance. It assumes that components have independent and identically distributed~(i.i.d.) lifetimes to describe only the impact of the system design on the system reliability and energy consumption. To this end, the Component Relevance is proposed to represent the probability that a component can keep its relevance throughout the system lifetime. Then, the Birnbaum Importance (BI) measure is applied to the system with ICM. The BI measure with ICM considers the relevance of the components while considering the reliability of the components. At the same time, the changes of the importance of the components in three different models, i.e., Perfect Fault Coverage Model (PFCM), Imperfect Fault Coverage Model (IFCM), and ICM, are analyzed. Moreover, the Dynamic Relevance Measure~(DRM) is defined to characterize the irrelevant components in different stages of the system lifetime depending on the number of occurred component failures, supporting the evaluation of the probability that the system fails due to uncovered failures of irrelevant components. Also, the gain in shutting down the irrelevant components in the ICM can be evaluated both in terms of the energy saved and the fraction of the average system lifetime during the system is not coherent. Finally, the system reliability over time is also efficiently derived, both in the case that irrelevance is not considered and in the case that irrelevant components can be immediately isolated, notably supporting any general (i.e.,~non-Markovian) distribution for the failure time of components. The feasibility and effectiveness of the proposed analysis methods are assessed on two real-scale case studies addressing the reliability evaluation of a flight control system and a multi-hop Wireless Sensor Network~(WSN). I have obtained the most important components for the left edge flap of the F18 flight control system to improve the component reliability, which improves system reliability more obviously. For the different topologies of WSN, the reliability and relevance of the Diagonal topology are better than the Orthogonal topology. So the WSN with Diagonal topology should be given priority in the system phase.