Chaonan Wang

Reliability of k-out-of-n systems with phased-mission requirements and imperfect fault coverage

In this paper, an efficient method is proposed for the exact reliability evaluation of k-out-of-n systems with identical components subject to phased-mission requirements and imperfect fault coverage. The system involves multiple, consecutive, and non-overlapping phases of operation, where the k values and failure time distributions of system components can change from phase to phase. The proposed method considers statistical dependencies of component states across phases as well as dynamics in system configuration and success criteria. It also considers the time-varying and phase-dependent failure distributions and associated cumulative damage effects for the system components. The proposed method is based on the total probability law, conditional probabilities and an efficient recursive formula to compute the overall mission reliability with the consideration of imperfect fault coverage. The main advantages of this method are that both its computational time and memory requirements are linear in terms of the system size, and it has no limitation on the type of time-to-failure distributions for the system components. Three examples are presented to illustrate the application and advantages of the proposed method.

Reliability analysis of multi-trigger binary systems subject to competing failures

This paper suggests two combinatorial algorithms for the reliability analysis of multi-trigger binary systems subject to competing failure propagation and failure isolation effects. Propagated failure with global effect (PFGE) is referred to as a failure that not only causes outage to the component from which the failure originates, but also propagates through all other system components causing the entire system failure. However, the propagation effect from the PFGE can be isolated in systems with functional dependence (FDEP) behavior. This paper studies two distinct consequences of PFGE resulting from a competition in the time domain between the failure isolation and failure propagation effects. As compared to existing works on competing failures that are limited to systems with a single FDEP group, this paper considers more complicated cases where the systems have multiple dependent FDEP groups. Analysis of such systems is more challenging because both the occurrence order between the trigger failure event and PFGE from the dependent components and the occurrence order among the multiple trigger failure events have to be considered. Two combinatorial and analytical algorithms are proposed. Both of them have no limitation on the type of time-to-failure distributions for the system components. Their correctness is verified using a Markov-based method. An example of memory systems is analyzed to demonstrate and compare the applications and advantages of the two proposed algorithms.

Competing failure analysis in phased-mission systems with functional dependence in one of phases

This paper proposes an algorithm for the reliability analysis of non-repairable phased-mission systems (PMS) subject to competing failure propagation and isolation effects. A failure originating from a system component which causes extensive damage to other system components is a propagated failure. When the propagated failure affects all the system components, causing the entire system failure, a propagated failure with global effect (PFGE) is said to occur. However, the failure propagation can be isolated in systems subject to functional dependence (FDEP) behavior, where the failure of a component (referred to as trigger component) causes some other components (referred to as dependent components) to become inaccessible or unusable (isolated from the system), and thus further failures from these dependent components have no effect on the system failure behavior. On the other hand, if any PFGE from dependent components occurs before the trigger failure, the failure propagation effect takes place, causing the overall system failure. In summary, there are two distinct consequences of a PFGE due to the competition between the failure isolation and failure propagation effects in the time domain. Existing works on such competing failures focus only on single-phase systems. However, many real-world systems are phased-mission systems (PMS), which involve multiple, consecutive and non-overlapping phases of operations or tasks. Consideration of competing failures for PMS is a challenging and difficult task because PMS exhibit dynamics in the system configuration and component behavior as well as statistical dependencies across phases for a given component. This paper proposes a combinatorial method to address the competing failure effects in the reliability analysis of binary non-repairable PMS. The proposed method is verified using a Markov-based method through a numerical example. Different from the Markov-based approach that is limited to exponential distribution, the proposed approach has no limitation on the type of time-to-failure distributions for the system components. A case study is given to illustrate such advantage of the proposed method.

A fast approximation method for reliability analysis of cold-standby systems

Analyzing reliability of large cold-standby systems has been a complicated and time-consuming task, especially for systems with components having non-exponential time-to-failure distributions. In this paper, an approximation model, which is based on the central limit theorem, is presented for the reliability analysis of binary cold-standby systems. The proposed model can estimate the reliability of large cold-standby systems with binary-state components having arbitrary time-to-failure distributions in an efficient and easy way. The accuracy and efficiency of the proposed method are illustrated using several different types of distributions for both 1-out-of-n and k-out-of-n cold-standby systems.

Reliability and lifetime modeling of wireless sensor nodes

Abstract The accuracy of system reliability analysis depends not only on system-level model construction, but also on realistic estimation of failure parameters at the component-level. In this paper, we model and evaluate the reliability and lifetime of a wireless sensor node under three typical working scenarios, contributing toward the accurate reliability analysis of wireless sensor network systems. According to the medium access control (MAC) protocols, the three working scenarios are defined based on the sensor node modes (sleep and active) and the mechanism of alternating between the modes. Reliability and lifetime of wireless sensor nodes under these three scenarios are illustrated and compared through numerical examples.

Reliability of Systems Subject to Failures With Dependent Propagation Effect

This paper suggests a method for the reliability analysis of binary-state systems subject to component failures with dependent propagation effect. A propagated failure originating from a system component causes extensive damage to the rest of the system. The level of the damage can be dependent upon the status of other system components and the order of the component failures. Such dependent propagation effect typically takes place in systems with some protection mechanism (e.g., firewalls, filters, and antivirus programs) or systems subject to functional dependence behavior where the failure of a system component, referred to as a trigger, causes other components within the same system to become inaccessible or isolated from the system. A combinatorial and analytical method is proposed for addressing the dependent propagation effect in the system reliability analysis. Basics and application of the proposed method are illustrated through analyses of an example of a network system in two different scenarios for propagation effects and an example of a memory system with multiple trigger events.

Probabilistic common cause failures in phased-mission systems

Probabilistic common cause failures (PCCFs) in a system are failures of multiple system components with the same or different probabilities due to a shared root cause or shock. They can contribute greatly to the overall system failure probability. Therefore, it is significant to incorporate effects of PCCFs into system reliability analysis. To the best of our knowledge, no research has been done on the reliability analysis of phased-mission systems (PMSs) subject to PCCFs. In this paper, we propose an explicit method and an implicit method to analyze reliability of PMSs with PCCFs caused by external shocks. Both methods are illustrated through detailed analyses of a wireless sensor network example. Both space and computational complexities as well as advantages are discussed and compared for the two proposed methods.

Explicit and implicit methods for probabilistic common-cause failure analysis

The occurrence of a probabilistic common-cause failure (PCCF) in a system results in failures of multiple system components with different probabilities. A PCCF can be caused by external shocks or propagated failures originating from some components within the system. This paper proposes an explicit method and an implicit method to analyze the reliability of systems subject to internal or external PCCFs. Both methods can handle any arbitrary types of time-to-failure distributions for the system components. Both of the proposed methods are illustrated through detailed analyses of an example computer system. Applicability and advantages are also discussed and compared for the two methods.

Competing failure analysis in phased-mission systems with multiple functional dependence groups

A phased-mission system (PMS) involves multiple, consecutive, non-overlapping phases of operation. The system structure function and component failure behavior in a PMS can change from phase to phase, posing big challenges to the system reliability analysis. Further complicating the problem is the functional dependence (FDEP) behavior where the failure of certain component(s) causes other component(s) to become unusable or inaccessible or isolated. Previous studies have shown that FDEP can cause competitions between failure propagation and failure isolation in the time domain. While such competing failure effects have been well addressed in single-phase systems, only little work has focused on PMSs with a restrictive assumption that a single FDEP group exists in one phase of the mission. Many practical systems (e.g., computer systems and networks), however may involve multiple FDEP groups during the mission. Moreover, different FDEP groups can be dependent due to sharing some common components; they may appear in a single phase or multiple phases. This paper makes new contributions by modeling and analyzing reliability of PMSs subject to multiple FDEP groups through a Markov chain-based methodology. Propagated failures with both global and selective effects are considered. Four case studies are presented to demonstrate application of the proposed method.

Competing failure analysis in non-repairable binary systems subject to functional dependence:

This paper considers competing failure propagation and isolation effects in the reliability analysis of systems with functional dependence, where the failure of some trigger component causes other components (referred to as dependent components) to become inaccessible or isolated from the system. A propagated failure originating from a dependent component could affect other parts of the system and thus cause the entire system to fail. However, if the trigger component fails first, the propagation of the dependent component failure can be prevented and thus it cannot affect the function of the rest of the system. In other words, propagated failures originating from dependent components in systems with functional dependence can have different consequences due to their competition with the failure of the trigger component in the time domain. This paper suggests a combinatorial method to address such competing failure behavior in the reliability analysis of non-repairable binary-state systems. Different from the work reported in the literature that assumes local and propagated failures of a component being mutually exclusive, the proposed method is applicable to independent and dependent local and propagated component failures. The system reliability analysis results for all the three cases (mutually exclusive, independent and dependent) are compared through a case study. The proposed method is verified through comparison with Markov-based methods.