Reliability modeling of on-surface transit systems with human errors

This paper presents two newly developed Markov models representing on-surface transportation systems subject to hardware failures and human errors. Transit system reliability, steady state availability, mean time to failure (MTTF) and variance of time to failure formulas are developed. Selective plots are shown for each model.     

并联电子系统级联失效可靠性分析与维护策略

与各部件失效相互独立的并联系统相比,级联失效这一因素显著降低了系统的可靠性。运用更新过程和马尔可夫理论。分析了存在级联失效关系的两同型部件并联系统的可靠性。为了有效地应对级联失效对并联电子设备系统的影响,引入了预防维护策略,并且建立了期望费用率模型．得到了使期望费用率最小的维护策略,最后给出了算例。     

Stochastic analysis of systems with primary and secondary failures

This paper presents the stochastic analysis of repairable systems involving primary as well as secondary failures. To this end, two models are considered. The first model represents a system with two identical warm standbys. The failure rates of units and the system are constant and independent while the repair times are arbitrarily distributed. The second system modeled consists of three repairable regions. The system operates normally if all three regions are operating, otherwise it operates at a derated level unless all three regions fail. The failure rates and repair times of the regions are constant and independent. The first model is analyzed using the supplemental variable technique while the second model is analyzed using the regenerative point technique in the Markov renewal process. Various expressions including system availability, system reliability and mean time to system failure are obtained.     

基于Markov过程的硬/软件综合系统可靠性分析

现代大型监控系统通常是一个复杂的硬/软件综合系统,其可靠性分析对于系统的设计、评估具有重要意义.综合考虑硬件、软件特点以及两者之间的相互作用关系,提出一种基于Markov过程的综合系统可靠性分析模型,模型中将系统失效分为硬件失效、软件失效与硬/软件结合失效.实际应用中,由于系统的状态数较大,提出利用循环网络方法对Markov状态转移方程进行求解,从而方便地得到系统处于各状态的瞬时概率与稳态概率.通过分析硬/软件综合系统可靠度、可用度与系统可靠性参数之间的关系,指出硬/软件结合失效将影响系统可用度,忽略硬/软件结合失效将导致可靠性估计值偏离实际值.     

ADS-B系统运行可靠性评价方法

为实现ADS-B系统运行可靠性的综合评价,提出了一种基于T-S模糊神经网络的方法。以平均首次故障时间、平均故障间隔时间、平均维修时间、平均可用度和维修时间率5项可靠性评价指标作为输入向量。利用T-S模糊系统构建可靠性综合评价的非线性映射关系,经神经网络的自适应训练,调整模糊规则和隶属度函数,建立ADS-B系统运行可靠性的综合评价模型。实验仿真与应用情况表明,该方法可行、有效,并具有较高的计算稳定性、精确性和良好的泛化能力,且评价结果客观、准确可靠,可作为提高ADS-B系统运行可靠性的决策依据。     

Availability analysis of a repairable standby human-machine system

This paper presents a model representing a two units active and one unit on standby human-machine system with general failed system repair time distribution. In addition, the model takes into consideration the occurrence of common-cause failures. The method of linear ordinary differential equation is presented to obtain general expressions for system steady state availability for failed system repair time distributions such as Gamma, Weibull, lognormal, exponential, and Rayleigh. Generalized expressions for system reliability, time-dependent availability, mean time to failure, and system variance of time to failure are also presented. Selected plots are presented to demonstrate the impact of human error on system steady state availability, reliability, time-dependent availability, and mean time to failure.     

Reliability modeling and assessment of the Star-Graph networks

The reliability of the Star Graph architecture is discussed. The robustness of the Star Graph network under node failures, link failures, and combined node and link failures is shown. The degradation of the Star Graph into Substar Graphs is used as the measure of system effectiveness in the face of failures. Models are provided for each of the failure and re-mapping modes evaluated herein, and the resilience of the Star Graph to failures is emphasized. This paper defines failure of a Star Graph as being when no fault-free (n - 1)-substars remain operational and the intermediate states are defined by the number of (n - 1)-substars that remain operational. A powerful tool (re-mapping) is introduced in which the number of operational (n 1)-substars can be maintained for longer periods, thus improving the overall MTTF (mean time to failure). For comparison the results of a similar reliability analysis of the hypercube is shown. The comparisons are considered conservative due to the failure model used herein for the star graph. One might apply re-mapping to hypercubes; while it would improve the overall MTTF of hypercubes, the hypercubes would still have an appreciably poorer performance than star graphs     

Dependability analysis for characterizing Google cluster reliability

Cloud solutions are emerging as a new suitable way of transforming traditional IT data centers to highly available and reliable computing resources for hosting critical applications and data. However, software and hardware failures are a common problem in cloud datacenters that can lead to harmful damages. In this paper, we analyze the physical server failures in the Google cloud datacenter. We study the Google cluster properties to investigate the relationship among physical servers' failure rate and jobs failure events. The failure rate of Google cluster executed jobs and servers is taken into consideration during a 29‐day period. We present a reliability model for Google cluster physical machines using the continuous time Markov chains according to this observation. We attempt to analyze the obtained model through SHARPE software packages to improve the understanding of failure events in the Google cloud cluster. We also explore the cluster availability based on parameters like steady‐state availability, steady‐state unavailability, mean time to failure, and mean time to repair in the Google cluster.     

Transient solutions of a software reliability model with imperfect debugging and error generation

In this paper we obtain transient solutions of a software reliability model under the assumption that the failure rate is proportional to the remaining errors in the software under imperfect debugging and error generation. The maximum number of errors in the software is assumed to be finite. We obtain the transient probabilities for the remaining errors, mean number of errors remaining, reliability of the software, expected number of failures etc. A method to estimate model parameters is given. Finally, a numerical example is presented.     

The branching nonhomogeneous Poisson process and its application to a replacement model

In studying and analysing the failure patterns of complex system, plausible stochastic models are needed to represent the sequence of events. A simple and frequently used model is derived by the assumption that the times-between-failures of a system are exponentially distributed and independent. Experience has shown, however, that successive times-between-failures are not exponentially distributed and not independent.These deviations are due to imperfect search of failed components. We constitute a plausible stochastic process which describes the sequence of events, and obtain the interval reliability and the expected number of failures.As an application of these results, we deal with the replacement model where a system undergoes minimal repair before time T and is replaced at time T. We discuss an optimum policy minimizing the total expected cost per unit time.     

Common-cause failures and critical human errors in repairable and non-repairable systems

This paper presents a reliability analysis of a k-out-of-N:G redundant system with common-cause failures, critical human errors and r repair facilities. The system is in a failed state when common-cause failures or critical human errors occurred or k units failed. When less than k units failed, the failed units are to be repaired. If the whole system is in a failed state, it cannot be repaired. Laplace transorms of state probabilities and system reliability are derived. Various versions of mean time to failure of a system are also reported.     

Reliability optimization models for embedded systems with multiple applications

Summary and Conclusions-This paper presents four models for optimizing the reliability of embedded systems considering both software and hardware reliability under cost constraints, and one model to optimize system cost under multiple reliability constraints. Previously, most optimization models have been developed for hardware-only or software-only systems by assuming the hardware, if any, has perfect reliability. In addition, they assume that failures for each hardware or software unit are statistically independent. In other words, none of the existing optimization models were developed for embedded systems (hardware and software) with failure dependencies. For our work, each of our models is suitable for a distinct set of conditions or situations. The first four models maximize reliability while meeting cost constraints, and the fifth model minimizes system cost under multiple reliability constraints. This is the first time that optimization of these kinds of models has been performed on this type of system. We demonstrate and validate our models for an embedded system with multiple applications sharing multiple resources. We use a Simulated Annealing optimization algorithm to demonstrate our system reliability optimization techniques for distributed systems, because of its flexibility for various problem types with various constraints. It is efficient, and provides satisfactory optimization results while meeting difficult-to-satisfy constraints.     

Reliability Assessment Of Computer System Design

This paper is intended to introduce a general purpose software and hardware design reliability assessment methodology based on the analysis of failure occurrence trend previous to modeling of failure processes. The failure data is collected at test phases and during the system operating life time. The maintenance requirement is used to qualify the Tropico R switching system, according to both hardware components and design failures.     

A birth-process approach to Moranda's geometric software-reliability model

To alleviate some of the objections to the basic Jelinski Moranda (JM) model for software failures, Moranda proposed a geometric de-eutrophication model. This model assumes that the times between failures are statistically-independent exponential random variables with given failure rates. In this model the failure rates decrease geometrically with the detection of a fault. Using an intuitive approach, Musa, Iannino, Okumoto , see also Farr , derived expressions for the mean and the intensity functions of the process N (t) which counts the number of faults detected in the time interval [O, t] for the Moranda geometric de-eutrophication model. N (t) is studied as a pure birth stochastic process; its probability generating function is derived, as well as its mean, intensity and reliability functions. The expressions for the mean and intensity functions derived by MIO are only approximations and can be quite different from the true functions for certain choices of the failure rates. The exact expressions for the mean function and the intensity function of N (t) are used to find the optimum release time of software based on a cost structure for Moranda's geometric de-eutrophication model.     

大型雷达装备使用可靠性评估

为查找制约大型雷达装备可靠性提高的薄弱环节,提高雷达战备完好性,建立了一种基于重要性的可靠性评估模型,并依据外场统计故障数据,利用该模型对某大型雷达发射系统的使用可靠性进行了评估。首先,针对大型雷达装备的特点,采用层次分析方法（AHP）,建立了具有3层评估指标的整机使用可靠性评估系统;其次,运用数理统计的方法,根据相同类型故障的寿命分布模型计算其可靠性指标;最后运用加权融合的方法获得部件系统及整机的平均故障间隔时间,用以评估雷达的使用可靠性,为大型雷达装备科学维修、设计改进以及新装备研制提供了参考。     

A system approach to reliability and life-cycle cost of processsafety-systems

An analytic method, PDS, allows the designer to assess the cost effectiveness of computer-based process safety-systems based on a quantification of reliability and life-cycle cost. Using PDS in early system design, configurations and operating philosophies can be identified in which the reliability of field devices and logic control units is balanced from a safety and an economic point of view. When quantifying reliability, the effects are included of fault-tolerant and fault-removal techniques, and of failures due to environmental stresses and failures initiated by humans during engineering and operation. A failure taxonomy allows the analyst to treat hardware failures, human failures, and software failures of automatic systems in an integrated manner. The main benefit of this taxonomy is the direct relationship between failure cause and the means used to improve safety-system performance     

Failure Time for a Redundant Repairable System of Two Dissimilar Elements

The distribution of time to failure for a system consisting of two dissimilar elements or subsystems operating redundantly and susceptible to repair is discussed. It is assumed that the times to failure for the two system elements are independent random variables from possibly different exponential distributions, and that the repair times peculiar to each element are independently distributed in an arbitrary fashion. For this basic model a derivation is given of the Laplace-Stieltjes transform of the distribution function of time to system failure, i.e, the time until both elements are simultaneously down for repair, measured from an instant at which both are operating. An explicit formula is given for the mean or expected time to system failure, a natural approximation to the latter is exhibited, and numerical comparisons indicate the quality of this approximation for various repair time distributions. In a second model the possibility of system failures due to overloading the remaining element after a single element failure is explicitly recognized. The assumptions made for the basic model are augmented by a stochastic process describing the random occurrence of overloads. Numerical examples are given. Finally, it is shown how the above models may be easily modified to account for delays in initiating repairs resulting from only occasional system surveillance, and to account for random catastrophic failures.     

A model for system reliability with common-cause failures

A model for the analysis of systems subject to common-cause failures is proposed. The system consists of a finite number of components that are subject to: (1) statistically independent failures, and (2) external failure causes (they need not be mutually statistically independent) for groups of components. Applications to fault-tree analysis and network reliability problems are discussed     

Predicting and eliminating built-in test false alarms

Failures detected by built-in test equipment (BITE) occur because a BITE measurement noise or bias as well as actual hardware failures. A quantitative approach is proposed for setting built-in test (BIT) measurement limits and this method is applied to the specific case of a constant failure rate system whose BITE measurements are corrupted by Gaussian noise. Guidelines for setting BIT measurement limits are presented for a range of system MTBF (mean time between failures) times and BIT run times. The technique was applied to a BIT for an analog VLSI test system with excellent results, showing it to be a powerful tool for predicting tests with the potential for false alarms. It was discovered that, for this test case, false alarms are avoidable