System Reliability Model Research Articles

엔진 유지점검과 정지능력을 고려한 액체로켓 추진시스템의 신뢰도 모형

Purpose: In this paper, we present a reliability model for a liquid rocket propulsion system with the engine out capability.<BR>Methods: Previously, researchers have developed such a reliability model, in which a failure decay function is used to modify time-independent reliability to time-dependent reliability for each engine. In that model, engine reliability at different thrust values was estimated independently, and the check-up time and mission time were fixed. Such a model is not useful for determining the check-up time necessary to achieve the system reliability target. In this paper, we present a system reliability model in terms of the engine check-up time and mission time. We use the cumulative exposure model to relate the lifetime of an engine operating at different thrust values, assuming that the lifetime of each engine follows a general distribution. By using a mixed exponential distribution, we obtain a closed form expression of system reliability and explain how time-independent engine reliability can be transformed to time-dependent engine reliability.<BR>Result: The proposed model is useful for determining the check-up time that provides the target mission reliability.<BR>Conclusion: The reliability of a liquid rocket propulsion system must be expressed explicitly in terms of the engine reliability depending on the check-up time and the mission time if the check-up time must be determined to achieve the system reliability requirement.

Reliability and hybrid maintenance modeling for competing failure systems with multistage periods

This paper deals with the reliability and hybrid maintenance models for systems which are subjected to competing and dependent failures due to degradation and external shocks. System studied here are with multistage periods, standby stage, working stage and the stop stage, which makes it different with previous literatures. The characters of degradation and external shocks vary with different periods and this also makes the proposed reliability model more challenging and more consistent with the engineering reality. Besides, a hybrid maintenance policy combined by age-based preventive maintenance and condition-based maintenance is studied by minimizing the average long-run maintenance cost. The optimal age-based preventive interval and the condition-based threshold are both calculated to manage the minimum maintenance cost. A numerical case demonstrates the availability and general applicability of proposed reliability and maintenance models at the end of this paper.

Unrepairable system with single production unit and n failure-prone identical parallel storage units

Despite the crucial role of product storage played in the operation of real-world systems, only very few reliability studies have considered this component in the system reliability modeling and analysis and the existing models assume only a single storage unit per system or subsystem. This paper makes advancements by modeling an unrepairable system with a production unit (PU) and multiple parallel storage units (SUs) of limited capacity. Both the PU and SUs are failure prone or imperfect with time-to-failure following arbitrary distributions. The surplus product in the case of the PU's performance exceeding the demand is evenly distributed among available SUs. The cumulated products in available SUs may subsequently compensate the deficiency when the PU fails or has insufficient performance. We put forward a numerical algorithm of evaluating the mission success probability (MSP) of the considered system with required demand and mission time. We conduct a case study on a water supply system with five SUs to illustrate the proposed model and investigate impacts of several model parameters (including initial SU filling, SU capacity, the number of SUs, PU productivity, reliabilities of PU and SU) as well as their interactions on the MSP.

Semi‐Markov reliability model of manufacturing systems considering machine degradation, human errors, and their mutual facilitation effects

AbstractReliability plays a significant role in the overall performance of manufacturing systems, and accurate reliability assessments can guarantee their functionalities and efficiencies. This paper develops a reliability model of a manufacturing system considering machine degradation, human errors, and their mutual facilitation effects (MFE): machine degradation may increase fatigue rate and weaken learning process, thereby facilitating the occurrence of human errors, while human errors may, in turn, facilitate the machine degradation process. Although MFE may reduce system reliability, current reliability models ignore this effect. In this paper, to describe the MFE, a stochastic human error model under the effects of learning–forgetting and fatigue–recovery is proposed, where the human error rate depends on the current machine degradation state; next, based on their facilitation effects on machine degradation, human errors are divided into safety, damage, and fatal zones; finally, we incorporate the zoned human error model into the machine degradation model and develop a Semi‐Markov reliability model. A Monte Carlo method is implemented to calculate system reliability. The turret of a lathe operated by a worker is utilized to illustrate the effectiveness of the reliability model.

Development of Predictive Reliability Model of Solar Photovoltaic System Using Stochastic Diffusion Process for Distribution System

Reliability assessment of power distribution systems is an essential concern for electric utilities to maintain supply continuity. In the event of supply failure, distributed energy resources play a vital role in restoring the supply to customers. This paper presents the development of a predictive reliability model for distribution system with solar Photovoltaic (PV) system. At the initial stage, the hourly solar irradiance and temperature are forecasted using Stochastic Diffusion Process (SDP)-based Monte Carlo simulation from historical data. Later, the cloud transients are modeled using the Jump Diffusion Process integrated into SDP. The monthly failure rates of PV system components are evaluated from historical data using the Physics of Failure (PoF) reliability model. Finally, the predictive reliability evaluation of the practical distribution system integrated with the proposed solar PV model is carried out. Results demonstrate the capability of the developed model to handle continuous and discrete uncertainties with more accuracy.

Statistical modeling and reliability analysis of multiple repairable systems with dependent failure times under perfect repair

In repairable systems, a fundamental aspect to be considered is to predict the reliability of the systems under study. Establishing reliability models for multiple repairable systems, however, is still a challenging problem when considering the dependency or unobserved heterogeneity of component failures. This paper focuses on a special repair assumption, called perfect repair, for repairable systems with dependent failures, where only the failed component is restored to as good as new condition. A frailty model is proposed to capture the statistical dependency and unobserved heterogeneity. The classical inferential method for estimating parameters and the reliability predictors will be shown for models in repairable systems under the assumption of perfect repair. An extensive simulation study is conducted under different scenarios to verify the suitability of the model and the asymptotic consistency and efficiency properties of the maximum likelihood estimators. The proposed methodology can be especially useful for industries that operate with repairable systems subjected to the replacement of parts after failures and to non-quantifiable factors that can interfere with the failure times of these parts. We illustrate the practical relevance of the proposed model on two real data sets. The first deals with a set of 9 sugarcane harvesters, observed during a fixed period of time, whose cutting blades failed several times in this interval. The other deals with a set of 5 dump trucks whose diesel engines also had recurring failures during the observation period. Parametric inference is carried out under the power-law process model that has found significant attention in industrial applications.

Reliability Analysis of Tape Winding Hydraulic System Based on Continuous-Time T-S Dynamic Fault Tree

It is necessary to make the tape winding system have good reliability. Because the power system usually is a pneumatic or hydraulic system, the static reliability analysis lacks the ability to describe the dynamic state transfer, component fault correlation, and propagation effect of the system; it is difficult to accurately reflect the actual behavior of the complex system. Most of the existing research results lack the situation that the importance of bottom events changes with time; only a single number cannot express the impact of bottom events on top events at different times. Therefore, this study uses the dynamic reliability analysis method to quantitatively analyze the reliability of the tape winding power hydraulic system. Firstly, the dynamic reliability model of hydraulic system is established by using the continuous-time T-S dynamic fault tree to solve the fault rate of the system. Secondly, the results are compared with the traditional Markov chain analysis method of dynamic fault tree. The feasibility and advantages of the continuous-time T-S dynamic fault tree analysis method are verified. Finally, the probability importance and key importance of the system unit are calculated, and the law of importance changing with time is expressed. According to the importance of different time, it can help the regular maintenance and fault diagnosis of equipment.

System Reliability Modeling and Analysis of Distributed Networks

The reliability of distributed network is researched by establishing one set of effective modeling, analysis, evaluation, and optimization method theory, which is a hot research area in the distributed network system field. The phased analysis method is utilized to study the reliability of the distributed network including the analysis and definition of the distributed network on the basis of studying its operational process. Meanwhile, task request, task scheduling, and execution phase will be also studied, and the establishment of reliability mathematical model of distributed network will be discussed to provide actual reference significance for the design of the distributed network system.

Reliability modeling of three-state systems with multiple types of components

In this paper, a system consisting of three states: perfect functioning, partial functioning, and down is considered. The system is assumed to be composed of several non-identical groups of binary components. The reliability of the system states under various assumptions on the component lifetimes is investigated. For this purpose, first, a new concept of bivariate survival signature (BSS) is introduced. Then, under the assumption that the component lifetimes of each type are exchangeable dependent, representations for the joint reliability function of the state lifetimes are obtained based on the notion of BSS. In the particular case, three-state systems composed of two types of different modules such as general-series (parallel) systems and systems with component-wise redundancy are investigated. Several examples are presented to illustrate the theoretical results.

Performance reliability analysis of multi-state degraded system with improved Lz transform

Universal Generating Functions and Lz transformations have been widely used in the reliability modeling of multi-state systems. In order to solve the problem of complex calculations due to the dense random combination of multi-state performance parameters in the Lz transformation, a screening function is defined before the Lz transformation, and the screening function is combined with the performance threshold to screening the state performance parameters in advance, and the process is simplified through the screen matrix and the screen block diagram, effectively reduce the combined dimensions and quantity, improve the efficiency of reliability analysis, and combine with specific examples for application verification.

Stress-strength reliability: a quantile approach

In reliability modelling and analysis of systems, quantile functions play a significant role when the distribution function under consideration does not possess an analytically tractable form, though the corresponding quantile function has an explicit form. In the present paper, we propose a quantile-based approach for stress-strength reliability of a system. We also introduce the quantile versions of stress-strength reliability for residual lifetime random variables. The effect of monotone transformations and some characterizations of the proposed measures are discussed. The reliability of multi-component stress-strength systems based on quantiles is also considered.

Dynamic Reliability Evaluation of High-Speed Train Gearbox Based on Copula Function

As a key component of the high-speed train transmission system, the reliability of the gearbox directly affects the reliability and driving safety of the high-speed train. Taking the key parts in the gearbox: driving gear, driven gear, gearbox housing and bearing as the research object, the dynamic reliability of the gearbox is evaluated. First, combined with classical stress-strength interference theory, the number of stochastic loads is regarded as a Poisson process, and the strength degradation is described by the Gamma process, the Gamma strength degradation parameter of each part is determined from the part material or the part’s P-S-N curve, and the reliability model of each key part of the gearbox is obtained. Second, the gearbox is regarded as a series system, and the Gumbel Copula function is introduced to deal with the nonlinear correlation between different parts and between different failure modes of the same part. The nesting relationship of the Copula function is determined, the parameter values of the Gumbel Copula function are determined based on the kernel density estimation and maximum likelihood estimation method, so as to establish the dynamic reliability model of the gearbox system and realize the evaluation of the dynamic reliability of the gearbox. The evaluation results show that the method for evaluating the reliability of high-speed train gearboxes is in line with engineering practice. The evaluation method has practical significance for the reliability check, optimization design and dynamic tracking of the gearbox reliability during the service period of the high-speed train gearbox.

Reliability Assessment in Rural Distribution Systems With Microgrids: A Computational- Based Approach

Rural distribution systems, especially in developing countries, tend to be less reliable than urban distribution systems because customers are (1) located remotely and (2) connected to weak aerial networks with radial topologies without redundancy. To improve reliability in rural areas, microgrids (MGs) are being integrated into conventional power systems. This study evaluates the effect on the reliability of rural distribution systems when MGs are introduced considering different penetration levels for renewable and nonrenewable distributed generation, and under rated power of energy storage. Here, we first formulate a reliability model for a rural distribution system with MGs. Based on this model, an interactive method using a sequential Monte Carlo simulation method is proposed and applied to calculate different conventional reliability indices. We show that this approach facilitates the selection of the parameters of the different systems constituting the MGs in order to comply with a predefined reliability objective. For instance, by introducing only photovoltaic distributed generation systems to the rural distribution systems under study, achieving the reliability objective is next to impossible. However, when correctly dimensioned-hybrid MGs are introduced, such an objective is successfully achieved. In the future, our model and the results provided herein could be combined with technical and economic studies to obtain an optimal solution that meets a certain reliability objective.

Resource Efficient Real-Time Reliability Model for Multi-Agent IoT Systems

Resource Efficient Real-Time Reliability Model for Multi-Agent IoT Systems

An evidential network-based hierarchical method for system reliability analysis with common cause failures and mixed uncertainties

Redundant design has been widely used in aerospace systems, nuclear systems, etc. which calls for particular attention to common cause failure problems in such systems with various kinds of redundant mechanisms. Besides, imprecision and epistemic uncertainties also need to be taken into account for system reliability modeling and assessment. In this paper, a comprehensive study based on the evidential network is performed for the reliability analysis of complex systems with common cause failures and mixed uncertainties. The decomposed partial α-factor is used to separate the contribution of independent parts and common cause parts of basic failure events. Mixed uncertainties are quantified and expressed by the D-S evidence theory, and the system reliability with uncertainties is modeled by evidential network. Furthermore, two layers, i.e. a decomposed event layer and coupling layer, are embedded into the evidential network of the system, and, as a result, the hierarchical structure of system reliability is constructed. The importance and sensitivities of various component types and their impact on system reliability are detected. The presented evidential network-based hierarchical method is applied to analyze the reliability of an auxiliary power supply system of a train and the results demonstrate the effectiveness of this method.

Reliability and availability models for ageing safety-related systems

This paper proposes reliability and availability models for ageing systems subject to failures detected on-line and (hidden) failures only revealed by proof tests, such as safety-related systems. Both types of failures are modelled by Weibull distributions with three parameters: shape, scale, and (virtual) age. For on-line detected failures (e.g. self-revealed or quickly detected by frequent automatic diagnostic tests), a corrective maintenance is assumed with a constant repair rate. For the other failures, a preventive maintenance consists in periodic proof tests that reveal the failures and, if applicable, a corrective maintenance is also performed. While the elements are assumed as bad as old (ABAO) after corrective maintenance, arithmetic reduction of age (ARA) with memory is considered for preventive maintenance. Analytical formulas are proposed for the time-dependent (virtual) age, failure rate, and unavailability of an element, for each type of failure. These formulas are implemented in a fault tree analysis tool for application to different architectures of systems with elements subject to different types of failures. For safety-related systems, results show that the use of the proposed models may prevent underestimating the unavailability of ageing systems (and therefore the risks) and enables definition of more appropriate maintenance policies.

Development of a dynamic event tree (DET) to analyze SBO accident in VVER-1000/V446 nuclear reactor

Probabilistic safety assessment (PSA) is the main approach currently applied in safety assessment of nuclear power plants to calculate the core damage frequency (CDF). The conventional event tree/fault tree methodology, adopted in current PSA studies, has weaknesses such as nonrealistic modeling of operator and recovery actions, inability for functional reliability modelling of passive safety systems, using predetermined timing and order of accident sequences without any interaction of system responses, insensitivity of the system failure to uncertainties in the process physics and consequently its output is not comprehensive for safety considerations, risk management and decision making tasks. In this study to overcome these bottlenecks, a dynamic approach based on dynamic event tree (DET) is applied to calculate the CDF for the station blackout (SBO) accident in VVER-1000/V446 nuclear reactor. To implement the DET, deterministic and probabilistic models are developed using the plant data and the characteristics of the SBO accident. These models are then run simultaneously to investigate the time of operator actions, AC power supply recovery, and the availability of safety systems on the accident progression and consequences. The results show that the value of CDF calculated with DET is equal to 1.97e-6 (yr−1). The results also illustrates that the DET can provide useful insights concerning potential risk contributors and the effectiveness of operator and recovery actions.

A reliability review on electrical collection system of battery energy storage power station

The battery energy storage system is a flexible resource with dual characteristics of source and load. It can be widely used in renewable energy consumption, peak shaving and frequency modulation, virtual power plant, and so on. However, the safety problem of energy storage system used in power system is serious, and it should be given an attention. In addition to being affected by the external operating environment of storage system, the reliability of its internal electrical collection system also plays a decisive role in the safe operation of energy storage power station. Therefore, for the reliability problem of battery energy storage power station, this paper analyzes the collection system structure, reliability model, evaluation algorithm and index system, establishes the single state reliability model of battery module considering derating state, presents a framework of a differentiated two-layer reliability evaluation algorithm for collection system of energy storage power station. This paper’s literature investigation can provide a support for the reliability improvement of energy storage power station.

Reliability evaluation of demand-based warm standby systems with capacity storage

Warm standby is an energy-saving redundancy technique that consumes less energy than a conventional hot standby method. It can be naturally integrated with an energy storage technique to enhance system reliability. However, the integration approach of both techniques and the advantage it affords to system reliability have not been reported in literature. This study resolves this limitation by formulating a novel reliability model for demand-based warm standby systems with capacity storage. In this model, the chronological characteristics of warm standby components are explicitly explored before and after their activation. Moreover, different utilization sequences of warm standby components and storage components are embedded to analyze the effects of these sequences on system reliability. A multi-valued decision diagram is developed to evaluate system reliability considering successful activation probabilities of warm standby components. This diagram is applicable to arbitrary component lifetime distributions and warm standby systems. Numerical examples are presented to verify the application of the proposed methodology.

Reliability analysis based on dynamic Bayesian networks: A case study of an unmanned surface vessel

Unmanned surface vessels (USVs) have been widely used in various activities to date. Reliability is particularly significant for USVs because of the increasing complexity of USV tasks and their characteristic that cannot be repaired during task execution. This study aims to analyse the reliability of USVs' overall system for providing an optimisation reference for their reliability improvement in the design phase. The method for modelling and analysing the reliability of complex systems based on Dynamic Bayesian Networks (DBNs) is studied. The reliability of a USV for seafloor topography survey is analysed. The reliability model of the USV overall system is established by mapping the Dynamic Fault Trees (DFTs) into DBNs considering the system logical structure, redundant configuration and dynamic behaviour. Reliability analysis, including reliability evaluation, importance measure and sensitivity analysis, are conducted on the basis of DBN inference. The overall reliability parameters of the USV are obtained to determine the critical subsystem and components. This research may provide a reference for the reliability design and optimisation of USVs.