基于率模可靠性的客观确定非对称概型功能函数隶属函数的方法

摒弃目前以主观方法给出功能函数对结构安全模糊集隶属函数的做法,提出并从理论上证明了：当功能函数具有非对称概型时,将功能函数的线性函数假想为集值统计的随机集边界点,通过定积分运算获得隶属函数的方法。算例充分说明文中方法的科学性和客观性。     

Single-use reliability computation of a semi-Markovian system

Markov chain usage models were successfully used to model systems and software. The most prominent approaches are the so-called failure state models Whittaker and Thomason (1994) and the arc-based Bayesian models Sayre and Poore (2000). In this paper we propose arc-based semi-Markov usage models to test systems. We extend previous studies that rely on the Markov chain assumption to the more general semi-Markovian setting. Among the obtained results we give a closed form representation of the first and second moments of the single-use reliability. The model and the validity of the results are illustrated through a numerical example.     

On signature-based expressions of system reliability

The concept of signature was introduced by Samaniego for systems whose components have i.i.d. lifetimes. This concept proved to be useful in the analysis of theoretical behaviors of systems. In particular, it provides an interesting signature-based representation of the system reliability in terms of reliabilities of k-out-of-n systems. In the non-i.i.d. case, we show that, at any time, this representation still holds true for every coherent system if and only if the component states are exchangeable. We also discuss conditions for obtaining an alternative representation of the system reliability in which the signature is replaced by its non-i.i.d. extension. Finally, we discuss conditions for the system reliability to have both representations.     

串并联可修系统的可靠性

本文通过密度演化法讨论了部件的寿命和修理时间都服从一般分布的由n个不同子系统串并联组成的可修系统的可靠性,为串并联系统的可靠性研究提供了理论依据.     

Interval uneffectiveness distribution for a k-out-of-n multistate reliability system with repair

This paper deals with a parallel load-sharing reliability system with cold standby redundancy and ample repair facilities. That is, we have n identical parallel units, of which at most k units are operating simultaneously. If less than k units are available, the system operates at a proportionally reduced level. For this system, an approximate method is given for the calculation of the probability distribution of that proportion of the system capacity that cannot be used in a given time period. The method is based on an approximation of the k-out-of-n multistate system by a two-state single component. Validation of the approximation using Monte-Carlo simulation shows satisfactory performance. Also, sensitivity results are given, showing in particular a decreasing sensitivity of the measures of performance to the distributional form of the unit lifetimes and repair times as the size of the system increases. Furthermore, it is found that the effect of the distributional form of the unit lifetimes dominates that of the unit repair times.     

Approximate confidence limits of the reliability performances for a cold standby series system

This paper is to investigate the approximate confidence limits of the reliability performances (such as failure rate, reliability function and average life) for a cold standby series system. The Bayesian approximate upper confidence limit of failure rate is obtained firstly, and next Bayesian approximate lower confidence limits for reliability function and average life are presented. The expressions for calculating Bayesian lower confidence limits of the reliability function and average life are also obtained, and an illustrative example is examined numerically by means of the Monte-Carlo simulation. Finally, the accuracy of confidence limits is discussed.     

Trend mining for system reliability employing a novel heuristic-based Kriging profiling method

This paper presents a novel integration of heuristic-based regressor for the prediction of system reliability. This is implemented by integrating single layer perceptron (SLP) into Kriging model on the basis of an enhanced Particle Swarm Optimization. The proposed method is labeled here as heuristic SLP-based Kriging, or in short HSK. The backbone of HSK is a Competitive Niching-inspired PSO (CNPSO) that serves as the heuristic for identifying the core parameters of the SLP-based Kriging. CNPSO is composed of an opposition-based competitive initialization and a niching-inspired search scheme. For practicality and validation purposes, realistic datasets in the literature of system reliability are considered in the present study. The experimental results obtained demonstrated that HSK outperformed state-of-the-art methods proposed in the literature for addressing the same issue.     

Estimation of system reliability for redundant stress-strength model

The reliability and an estimate for it are derived for series-parallel and parallel-series stress-strength model under assumption that all components are subjected to a common stress. We also obtain the asymptotic normal distribution of the estimate.     

A system reliability approach to linear programming

Summary A system reliability approach to linear programming is developed here for the case when the restrictions are chance-constrained. Methods of characterizing a system reliability measure for a linear programming system, its implications under alternative probability distribution assumptions and its uses for specifying policies with an improved system reliability routine are analytically discussed.

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Zusammenfassung In der vorliegenden Arbeit wird ein Verfahren zur Untersuchung der Zuverlässigkeit eines Systems für den Fall entwickelt, daß die Beschränkungen eines L. P.-Problems zufallsabhängig sind. Es werden Methoden zur Charakterisierung eines Maßes für die Zuverlässigkeit eines L. P.-Systems, die sich daraus ergebenden Implikationen bei verschiedenen Annahmen über die Wahrscheinlichkeitsverteilung und die Möglichkeit zur Bestimmung von Politik-Arten mittels eines verbesserten Verfahrens zur Untersuchung der System-Zuverlässigkeit diskutiert.

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Work done under the National Science Foundation Project GS 1810/420-41-17 at the Department of Economics, Iowa State University. This work develops the theoretical ideas originally fromulated in a paper by this author: Safety first rules under chance-constrained linear programming.Operations Research: The Journal of Operations Research Society of America, Vol.17, No. 1, 1969, pp. 112–132.

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Vorgel. v.:W. Wittmann     

Optimization of system reliability by adaptive randomly directed search

A new adaptive randomly directed search algorithm was developed for optimizing the reliability of a system employing redundancy. This algorithm can handle general nonlinear integer formulations. Its usefulness and advantages in solving reliability problems were demonstrated through three examples given in the literature.     

Interval estimation of system reliability using a conditional distribution function of the number of failures

Interval estimators of the no-failure probability of a system are constructed from tests of system elements. The estimators are obtained using the conditional distribution function of the number of failures during the tests.Translated from Statisticheskie Metody Otsenivaniya i Proverki Gipotez, pp. 58–64, 1986.     

Reliability stochastic optimization for a series system with interval component reliability via genetic algorithm

This paper deals with chance constraints based reliability stochastic optimization problem in the series system. This problem can be formulated as a nonlinear integer programming problem of maximizing the overall system reliability under chance constraints due to resources. The assumption of traditional reliability optimization problem is that the reliability of a component is known as a fixed quantity which lies in the open interval (0, 1). However, in real life situations, the reliability of an individual component may vary due to some realistic factors and it is sensible to treat this as a positive imprecise number and this imprecise number is represented by an interval valued number. In this work, we have formulated the reliability optimization problem as a chance constraints based reliability stochastic optimization problem with interval valued reliabilities of components. Then, the chance constraints of the problem are converted into the equivalent deterministic form. The transformed problem has been formulated as an unconstrained integer programming problem with interval coefficients by Big-M penalty technique. Then to solve this problem, we have developed a real coded genetic algorithm (GA) for integer variables with tournament selection, uniform crossover and one-neighborhood mutation. To illustrate the model two numerical examples have been solved by our developed GA. Finally to study the stability of our developed GA with respect to the different GA parameters, sensitivity analyses have been done graphically.     

The reliability analysis of probabilistic and interval hybrid structural system

The aim of this paper is to evaluate the reliability of probabilistic and interval hybrid structural system. The hybrid structural system includes two kinds of uncertain parameters—probabilistic parameters and interval parameters. Based on the interval reliability model and probabilistic operation, a new probabilistic and interval hybrid reliability model is proposed. Firstly, we use the interval reliability model to analyze the performance function, and then sum up reliability of all regions divided by the failure plane. Based on the presented optimal criterion enumerating the main failure modes of hybrid structural system and the relationship of failure modes, the reliability of structure system can be obtained. By means of the numerical examples, the hybrid reliability model and the traditional probabilistic reliability model are critically contrasted. The results indicate the presented reliability model is more suitable for analysis and design of these structural systems and it can ensure the security of system well, and it only needs less uncertain information.     

Fuzzy Bayesian system reliability assessment based on exponential distribution

The Bayesian system reliability assessment under fuzzy environments is proposed in this paper. In order to apply the Bayesian approach, the fuzzy parameters are assumed as fuzzy random variables with fuzzy prior distributions. The (conventional) Bayesian estimation method will be used to create the fuzzy Bayes point estimator of system reliability based on Exponential distribution by invoking the well-known theorem called “Resolution Identity” in fuzzy sets theory. On the other hand, we also provide the computational procedures to evaluate the membership degree of any given Bayes point estimate of system reliability. In order to achieve this purpose, we transform the original problem into a nonlinear programming problem. This nonlinear programming problem is then divided into four subproblems for the purpose of simplifying computation. Finally, the subproblems can be solved by using any commercial optimizers, e.g., GAMS or LINGO (LINDO).     

Optimal allocation of reliability tasks to mitigate faults during system development

^** Email: walter.johnston{at}baesystems.com^*** Email: j.quigley{at}strath.ac.uk^**** Email: lesley.walls{at}strath.ac.uk This paper considers reliability planning for a concept designfor a new system where a portfolio of possible reliability developmenttasks exists; the goal is to find a selection and sequence oftasks to achieve reliability targets subject to time constraintsat minimal cost. This is non-trivial given that each task potentiallycan expose several different weaknesses and each weakness potentiallycan be exposed by several different tasks. We use a Bayesianpoint process model to estimate the system reliability. Theprior distribution maps to a fault register and relates directlyto a set of potential engineering modifications.The likely impactof each task can be assessed using the point process model.An integer programming approach is used to sequence and scheduletasks under the constraint that contractual reliability requirementsmust be met. An illustrative example is provided and an extensionto system availability is proposed.     

Functions of elementary random variables and their application to system reliability

Summary LetX ₁,...,X _n be elementary random variables, i.e. random variables taking only finitely many values in . Then for an arbitray functionf(X ₁,...,X _n ) inX ₁,...,X _n a unique polynomial representation with the aid of Lagrange polynomials is given. This easily yields the moments as well as the distribution off(X ₁,...,X _n ) by terms of finitely many moments of the variablesX ₁,...,X _n . For n=1 a necessary and sufficient condition results thatm numbers are the firstm moments of a random variable takingm+1 different values. As an application of random functionsf(X ₁,...,X _n ) the reliability of technical systems with three states is treated.

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Zusammenfassung X ₁, ...,X _n seien elementare Zufallsvariable, d. h., Zufallsvariable, die nur endlich viele reelle Werte annehmen. Mit Hilfe von Lagrangepolynomen wird für eine beliebige Funktionf(X₁,...,X _n ) eine eindeutige polynomiale Darstellung angegeben. Daraus ergeben sich leicht die Momente wie auch die Verteilung von f(X₁,...,X _n ), ausgedrückt durch die Momente der VariablenX ₁,...,X _n . Fürn=1 erhält man eine notwendige und hinreichende Bedingung, daßm Zahlen die erstenm Momente einer Zufallsvariablen sind, diem+1 verschiedene Werte annimmt. Als Anwendung wird die Zuverlässigkeit eines technischen Systems mit drei Zuständen behandelt.

     

Planning performance based contracts considering reliability and uncertain system usage

This paper investigates a novel quantitative approach for planning and contracting performance-based logistics in the presence of uncertain system usage. Our efforts focus on an integrated service delivery environment where the manufacturer develops capital-intensive systems and also provides after-sales support. We propose an analytical model to characterize system operational availability by comprehending five performance drivers: inherent failure rate, usage rate, spare parts inventory, repair time, and the fleet size. This analytical insight into the system performance allows the service supplier to minimize the total cost across system design, production, maintenance, and repair. Two contracting schemes are investigated under cost minimization and profit maximization schemes. For the first time in literature, reliability design and service parts logistics are seamlessly integrated into one decision support model for improving operational availability while lowering the lifecycle cost. Numerical examples are provided to demonstrate the applicability and the effectiveness of the proposed decision support tool.     

Estimation of system reliability in Brownian stress-strength models based on sample paths

Reliability of many stochastic systems depends on uncertain stress and strength patterns that are time dependent. In this paper, we consider the problem of estimating the reliability of a system when bothX(t) andY(t) are assumed to be independent Brownian motion processes, whereX(t) is the system stress, andY(t) is the system strength, at timet.This research was partially supported by the Air-Force Office of Scientific Research Grants AFOSR-89-0402 and AFOSR-90-0402.