Component Reliability Importance Research Articles

Reliability Analysis and Imprecise Component Importance Measure of Redundant Systems of OWTs Based on Component Swapping

Due to the high cost of failures of wind turbines, redundancy designs are commonly applied in wind turbines for improving the reliability and availability of systems. For this reason, replacing failed components with other working components of the same type in redundant systems is becoming an attractive option of maintenance strategies towards more resilient systems. To quantitatively evaluate system’s reliability, this paper focuses on the reliability analysis of redundant systems of offshore wind turbines based on swapping existing components. The survival signature-based component swapping method is introduced to describe the new structure-function of the system upon swapping. Furthermore, the reliability model of redundant systems is established using the fault tree and survival signature. Following this, the influences of component swapping on component reliability importance measure (marginal reliability importance and joint reliability importance) without and with considerations of the imprecision of failure rates are explored. Finally, a 5MW offshore wind turbine is presented to show the applicability of the proposed approach for redundant systems, and the results show that the proposed approach can obtain realistic reliability assessment of redundant systems and considering component swapping can significantly improve system reliability.

A new hybrid reliability allocation method, based on developed ME-OWA method, Birnbaum importance measure and fuzzy DEMATEL technique

Reliability allocation is an important subject in designing products and systems. Maximal entropy ordered weighted averaging (ME-OWA) approach based on DEMATEL allocation method has been developed to cover some of the problems of the subject. However, there are some unexplained critical issues in measurement scale, weights of the allocation factors, considering relations between components, and respecting predicted failure rates that considering them in the mentioned method can result in a more comprehensive reliability allocation scheme in covering the problems. Moreover, the reliability importance of system components, and the fuzziness in DEMATEL method data are not considered in the ME-OWA-based DEMATEL allocation method. To address these issues in this paper, a new hybrid approach is proposed which is based on new ME-OWA weights, Birnbaum importance measure, and fuzzy DEMATEL technique. The results of implementing the new hybrid method on a fighter aircraft's digital flight control computer indicate several benefits of the new developed scheme in considering the stated concerns.

A new hybrid reliability allocation method, based on developed ME-OWA method, Birnbaum importance measure and fuzzy DEMATEL technique

Reliability allocation is an important subject in designing products and systems. Maximal entropy ordered weighted averaging (ME-OWA) approach based on DEMATEL allocation method has been developed to cover some of the problems of the subject. However, there are some unexplained critical issues in measurement scale, weights of the allocation factors, considering relations between components, and respecting predicted failure rates that considering them in the mentioned method can result in a more comprehensive reliability allocation scheme in covering the problems. Moreover, the reliability importance of system components, and the fuzziness in DEMATEL method data are not considered in the ME-OWA-based DEMATEL allocation method. To address these issues in this paper, a new hybrid approach is proposed which is based on new ME-OWA weights, Birnbaum importance measure, and fuzzy DEMATEL technique. The results of implementing the new hybrid method on a fighter aircraft's digital flight control computer indicate several benefits of the new developed scheme in considering the stated concerns.

Reliability and Maintenance Prioritization Analysis of Combined Cooling, Heating and Power Systems

A combined cooling, heating, and power (CCHP) system is a complex and repairable system containing a large number of components and series of subsystems. When a failure occurs in one component, it might cause a failure of a subsystem or whole system. Traditional maintenance methods might lead to the waste of maintenance resources and a high cost of maintenance. The reliability and maintenance prioritization analyses can help managers optimize maintenance strategies and reduce the total cost. A reliability importance index is one of the factors in maintenance prioritization analysis. This paper aims at selecting the component reliability importance indices to identify the priority of component maintenance of a CCHP system from the perspective of maintenance cost. Failure cost importance index (FCI) and Potential failure cost importance index (PI) are developed for the maintenance prioritization analysis of a CCHP system. A Markov model based on the state–space method (SSM) is used to analyze the reliability and availability of a CCHP system. A set of actual survey reliability data of CCHP systems is used to support the validity of the reliability importance indices. The results indicate that the FCI and PI might lead to different rankings of maintenance prioritization. The FCI and PI will help managers make a reasonable decision for maintenance on a cost basis.

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

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.

Reliability sensitivity analysis of coherent systems based on survival signature

The reliability sensitivity can be used to rank distribution parameters of system components concerning their impacts on the system’s reliability. Such information is essential to purposes such as component prioritization, reliability improvement, and risk reduction of a system. In this article, we present an efficient method for reliability sensitivity analysis of coherent systems using survival signature. The survival signature is applied to calculate the reliability of coherent systems. The reliability importance of components is derived analytically to evaluate the relative importance of the component with respect to the overall reliability of the system. The closed-form formula for the reliability sensitivity of the system with respect to component’s distribution parameters is derived from the derivative of lifetime distribution of a component to further investigate the impacts of the distribution parameters on the system’s reliability. The effectiveness and feasibility of the proposed approaches are demonstrated with two numerical examples.

Reliability Optimization and Importance Analysis of Circular-Consecutive k-out-of-n System

The circular-consecutive k-out-of-n:F(G) system (Cir/Con/k/n:F(G) system) usually consists of n components arranged in a circle where the system fails (works) if consecutive k components fail (work). The optimization of the Cir/Con/k/n system is a typical case in the component assignment problem. In this paper, the Birnbaum importance-based genetic algorithm (BIGA), which takes the advantages of genetic algorithm and Birnbaum importance, is introduced to deal with the reliability optimization for Cir/Con/k/n system. The detailed process and property of BIGA are put forward at first. Then, some numerical experiments are implemented, whose results are compared with two classic Birnbaum importance-based search algorithms, to evaluate the effectiveness and efficiency of BIGA in Cir/Con/k/n system. Finally, three typical cases of Cir/Con/k/n systems are introduced to demonstrate the relationships among the component reliability, optimal permutation, and component importance.

Component Reliability Importance assessment on complex systems using Credible Improvement Potential

Nowadays system reliability performance represents a key issue and being reliable becomes a fundamental requirement of products in many manufacturing fields. The paper is focused on the reliability improvement of fault tolerant complex systems using component Reliability Importance (RI) procedures in order to assess the impact of each component on the overall system reliability. This study is focused on RI assessment during design stage with the aim of optimizing engineers' efforts and focusing on components with the greatest effect on the whole system. The first part of the paper focuses on a particular Reliability Importance measure, the Credible Improvement Potential (CIP), which is the most suitable RI metric for our purpose. The Reliability Importance assessment on a dedicated case study based on fault tolerant complex system is then proposed and results are discussed in detail.

Multicomponent joint reliability importance of series-in-parallel and parallel-in-series systems

Purpose – Joint reliability importance (JRI) of components is the effect of a change of their reliability on the system reliability. The authors consider two coherent multi-component systems – a series-in-parallel (series subsystems arranged in parallel) and a parallel-in-series (parallel subsystems arranged in series) system. It is assumed that all the components in the subsystems are independent but not identically distributed. The subsystems do not have any component in common. The paper aims to discuss these issues. Design/methodology/approach – For both the systems, the expressions for the JRI of two or more components are derived. The results are extended to include subsystems where some of the components are replicated. Findings – The findings are illustrated by considering bridge structure as a series-in-parallel system wherein some of the components are repeated in different subsystems. Numerical results have also been provided for a series-in-parallel system with unreplicated components. JRI for various combinations of components for both the illustrations are given through tables or figures. Originality/value – Chang and Jan (2006) and Gao et al. (2007) found the JRI of two components of series-in-parallel system when the components are identical and independently distributed. The authors derive the JRI of m=2 components for series-in-parallel and parallel-in-series systems when components are independent but need not be identically distributed. Expressions are obtained for the above-mentioned systems with replicated and unreplicated components in different subsystems. These results will be useful in analyzing the joint effect of reliability of several components on the system reliability. This will be of value to design engineers for designing systems that function more effectively and for a longer duration.

Importance analysis for reconfigurable systems

Importance measures are used in reliability engineering to rank the system components according to their contributions to proper functioning of the entire system and to find the most effective ways of reliability enhancement. Traditionally, the importance measures do not consider the possible change of system structure with the improvement of specific component reliability. However, if a component׳s reliability changes, the optimal system structure/configuration may also change and the importance of the corresponding component will depend on the chosen structure. When the most promising component reliability improvement is determined, the component importance should be taken into account with respect to the possible structure changes. This paper studies the component reliability importance indices with respect to the changes of the optimal component sequencing. This importance measure indicates the critical components in providing the system reliability enhancement by both enhancing the component׳s reliability and reconfiguring the system. Examples of linear consecutive-k-out-of-n: F and G systems are considered to demonstrate the change of the component Birnbaum importance with the optimal system reconfiguration. The results show that the change of the importance index corresponds to the change of the system optimal configuration and the importance index can change not monotonically with the variation of the component reliability.

BIRNBAUM IMPORTANCE FOR CONSECUTIVE-k SYSTEMS

Reliability importance of components of various systems is an important part in the reliability study. In this paper Birnbaum-reliability importance (B-importance) of components of three popular consecutive-type systems as consecutive-k-out-of-n: F-system, m-consecutive-k-out-of-n: F system and r-within-consecutive-k-out-of-n: F system is studied. The B-importance is studied when the survival probabilities of components of the system are Markov dependent. This study is based on conditional distribution of number of occurrences of failure runs of length k and number of occurrences of scanning windows of length k containing r failures in the sequence of Markov Bernoulli trials. Simplified formulae for calculation of B-importance of each component of the three consecutive-type systems are developed in terms of survival probabilities. To demonstrate the simplicity of the derived results, numerical study is also included.

Component Reliability Importance Measure in Presence of Transient Faults

Importance measures are widely used to characterize the contribution of components to the system performance such as reliability, availability, risk, etc, and thus give great help in identifying system weaknesses and prioritizing system improvement activities. Although much work has been carried out on component importance analysis, most studies only concern the consistent states of components within which components exhibit consistent performance until state changes happen. Unfortunately, field data shows that many transient faults in components may result in severe consequences without causing any state changes, and, this can lead to a misunderstanding of component importance. This paper focuses on the reliability importance analysis in presence of transient faults, and proposes a composite measure for evaluation. A sample series parallel system is analyzed to illustrate the use of this measure.

The reliability importance of components and prime implicants in coherent and non-coherent systems including total-order interactions

In the management of complex systems, knowledge of how components contribute to system performance is essential to the correct allocation of resources. Recent works have renewed interest in the properties of the joint ( J) and differential ( D) reliability importance measures. However, a common background for these importance measures has not been developed yet. In this work, we build a unified framework for the utilization of J and D in both coherent and non-coherent systems. We show that the reliability function of any system is multilinear and its Taylor expansion is exact at an order T. We then introduce a total order importance measure ( D T ) that coincides with the exact portion of the change in system reliability associated with any (finite or infinitesimal) change in component reliabilities. We show that D T synthesizes the Birnbaum, joint and differential importance of all orders in one unique indicator. We propose an algorithm that enables the numerical estimation of D T by varying one probability at a time, making it suitable in the analysis of complex systems. Findings demonstrate that the simultaneous utilization of D T and J provides reliability analysts with a complete dissection of system performance.

Reliability Analysis for Various Communication Schemes in Wireless CORBA

For the purpose of designing more reliable networks, we extend the traditional reliability analysis from wired networks to wireless networks with imperfect components. Wireless network systems, such as wireless CORBA, inherit the unique handoff characteristic which leads to different communication structures with various components & links. Therefore, the traditional definition of two-terminal reliability is not applicable any more. We propose a new term, end-to-end expected instantaneous reliability, to integrate those different communication structures into one metric, which includes not only failure parameters but also service parameters. Nevertheless, it is still a monotonously decreasing function of time. The end-to-end expected instantaneous reliability, and its corresponding MTTF, are evaluated quantitatively in different wireless communication schemes. To observe the gain in overall reliability improvement, the reliability importance of imperfect components are also evaluated. The results show that the failure parameters of different components take different effects on MTTF & reliability importance. With different expected working time of a system, the focus of reliability improvement should change from one component to another in order to receive the highest reliability gain. Furthermore, the number of engaged components during a communication state is more critical than the number of system states. For simplicity, we assume that the wired & wireless communication links are perfect, and omit them in the reliability analysis. If these two are engaged into the proposed end-to-end expected instantaneous reliability, it can give a more detailed & complete reliability assessment of a wireless network system. Our quantitative measurements are conducted as an example with the assumption that the failure & service rate are constant; however, in practice, failure & service processes may follow other distributions. After all, our investigation provides an initial yet overall approach to measure the reliability of wireless networks. Although our analysis is conducted on wireless CORBA platforms, it is easily extensible to generic wireless network systems.

Importance measures for non-coherent-system analysis

Component importance analysis is a key part of the system reliability quantification process. It enables the weakest areas of a system to be identified and indicates modifications, which will improve the system reliability. Although a wide range of importance measures have been developed, the majority of these measures are strictly for coherent system analysis. Noncoherent systems can occur and accurate importance analysis is essential. This paper extends four commonly used measures of importance, using the noncoherent extension of Birnbaum's measure of component reliability importance. Since both component failure and repair can contribute to system failure in a noncoherent system, both of these influences need to be considered. This paper highlights that it is crucial to choose appropriate measures to analyze component importance. First the aims of the analysis must be outlined and then the roles that component failures and repairs can play in system state deterioration can be considered. For example, the failure/repair of components in safety systems can play only a passive role in system failure, since it is usually inactive, hence measures that consider initiator importance are not appropriate to analyze the importance of these components. Measures of importance must be chosen carefully to ensure analysis is meaningful and useful conclusions can be drawn.

Mathematical Theory of Reliability of Time Dependent Systems with Practical Applications

Markov and Semi-Markov Models as a Basis for the Mathematical Analysis of System Reliability. Methods for Investigating Homogeneous and Non-Homogeneous Point Processes (Event Flows). Fault Trees--The Current State of Research. Theory of Redundant Systems. Monte Carlo Methods. Reliability Analysis using Perturbation Methods. Stiff Processes in Reliability Analysis. Variance Reduction Methods. Analytical-Statistical Methods for Rapid Simulation of Repairable Systems with Structure Redundancy. Measures of Reliability Importance of Components. Index.

A suggestion of a new measure of system components importance by means of a Boolean difference

The new measures of reliability importance of coherent system's components are introduced based on a concept of a Boolean difference. A case of two components is studied and various importance measures named weight, contribution and significance are treated. The results can be generalized for more than two components and for measures of survivance and safety as well.

A new heuristic method redundancy optimization in a consecutive- k-out-of- n:F system by fuzzy probability

In this paper it is presented heuristic method and its modification for solution of the redundancy optimization problem by fuzzy failure probabilities. This method is considered for consecutive-k-out-of-n:F system due to simplified expression for reliability importance of components. Method is based on the fuzzification and on the fuzziness importance of failure probabilities.

Reliability For High System Utilization

This paper explores new applications of the consecutive-k-out of-n systems. presents the Birnbaum component reliability importance pattern for the consecutive-2-out-of-n systems. conjectures on the optimal system design of the consecutive-kout- of-n systems. and points out research directions for the optimal design of the consecutive-k-out-of-n systems.

A consecutive-k-out-of-n:G system: the mirror image of a consecutive-k-out-of-n:F system

A consecutive-k-out-of-n:F (consecutive-k-out-of-n:G) system consists of an ordered sequence of n components such that the system is failed (good) if and only if at least k consecutive components in the system are failed (good). In the present work, the relationship between the consecutive-k-out-of-n:F system and the consecutive-k-out-of-n:G system is studied, theorems for such systems are developed, and available results for one type of system are applied to the other. The topics include system reliability, reliability bounds, component reliability importance, and optimal system design. A case study illustrates reliability analysis and optimal design of a train operation system. An optimal configuration rule is suggested by use of the Birnbaum importance index.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>