Reliability Measures Of System Research Articles

Calculation of Travel Time Variability from Loop Detector Data

Travel time variability has recently become an important measure in transportation system management and has begun to be treated as a major factor influencing travel decisions. The main purpose of this study is to develop a database to help understand traffic variability of point measures and route-level measures by incorporating existing traffic surveillance systems. This study develops an integrated geographic information system database for traffic analysis in Orange County, California, and reports temporal and spatial traffic variability as measures of travel reliability. The database is to provide the analysis framework to study travel time variability at both the section level and the route level. In many cases, traffic data are used for traffic operations without the data being stored. The archived traffic data can play an important role as a way of measuring freeway performance. Such historic data make it possible to analyze such travel time variability from a long-term perspective. The database developed in this study is expected to help researchers and practitioners understand travel time variability as a measure of transportation system reliability by providing the analysis framework.

Calculation of Travel Time Variability from Loop Detector Data

Travel time variability has recently become an important measure in transportation system management and has begun to be treated as a major factor influencing travel decisions. The main purpose of this study is to develop a database to help understand traffic variability of point measures and route-level measures by incorporating existing traffic surveillance systems. This study develops an integrated geographic information system database for traffic analysis in Orange County, California, and reports temporal and spatial traffic variability as measures of travel reliability. The database is to provide the analysis framework to study travel time variability at both the section level and the route level. In many cases, traffic data are used for traffic operations without the data being stored. The archived traffic data can play an important role as a way of measuring freeway performance. Such historic data make it possible to analyze such travel time variability from a long-term perspective. The database developed in this study is expected to help researchers and practitioners understand travel time variability as a measure of transportation system reliability by providing the analysis framework.

Structural optimization of linear dynamical systems under stochastic excitation: a moving reliability database approach

A method to carry out structural synthesis of deterministic linear dynamical systems under stochastic excitation is introduced. The structural optimization problem is written as a nonlinear mathematical programming problem with reliability constraints. Probability that design conditions are satisfied within a given time period is used as a measure of system reliability. The solution of the original optimization problem is replaced by the solution of a sequence of approximate sub-optimization problems. An explicit approximation of the system reliability in terms of the design variables is constructed in each sub-optimization problem. The approximations are locally adjusted to a reliability database, which is obtained by an efficient importance sampling technique. Each approximate optimization problem is solved in an efficient manner due to the availability of the system reliability in explicit form. Numerical examples are presented to illustrate the performance and efficiency of the proposed methodology.

A new efficient algorithm for computing the imprecise reliability of monotone systems

Reliability analysis of complex systems by partial information about reliability of components and by different conditions of independence of components may be carried out by means of the imprecise probability theory which provides a unified framework (natural extension, lower and upper previsions) for computing the system reliability. However, the application of imprecise probabilities to reliability analysis meets with a complexity of optimization problems which have to be solved for obtaining the system reliability measures. Therefore, an efficient simplified algorithm to solve and decompose the optimization problems is proposed in the paper. This algorithm allows us to practically implement reliability analysis of monotone systems under partial and heterogeneous information about reliability of components and under conditions of the component independence or the lack of information about independence. A numerical example illustrates the algorithm.

Interval reliability of typical systems with partially known probabilities

Most probabilistic methods of the system reliability analysis assume that the component lifetime distributions are known precisely and the system components are independent. The paper considers reliability analysis of typical systems when the above assumptions are violated and there is only some partial information about the component lifetime distributions. The analysis is based on considering sets of possible probability distributions consistent with available information. All resulting expressions are obtained in the explicit form. The impact of incompleteness of initial data on the resulting system reliability measures is illustrated by a numerical example.

Reliability of multi-state systems with two failure-modes

Systems with two failure modes (STFM) consist of devices, which can fail in either of two modes. For example, switching systems can not only fail to close when commanded to close but can also fail to open when commanded to open. This paper considers systems consisting of different elements characterized by nominal performance level in each mode. Such systems are multi-state because they have multiple performance levels in both modes, depending on the combination of elements available at the moment. The system availability is defined as the probability of satisfaction of given constraints imposed on system performance in both modes. The paper suggests reliability measures for multi-state systems with 2 failure modes, and presents a procedure for evaluating these measures. The procedure is based on the use of a universal moment generating function (UMGF). It allows one to estimate availability and s-expected performance of complex systems with series-parallel and bridge topology. Basic UMGF technique operators are developed for two types of systems, based on transmitting-capacity and on operation-time.

A second-order uncertainty model for calculation of the interval system reliability

Abstract A second-order uncertainty model of the system reliability is studied in the paper. This model takes into account the fact that the reliability description of the system components is unreliable itself and has some degree of belief to it. It is assumed that there is no information about probability distributions on both first and second levels of the proposed second-order uncertainty model, the available information about the reliability of the system components is heterogeneous, and there is no information about independence of the system components. Algorithms for computing beliefs to the system reliability measures and for reducing the second-order model to the first-order one are proposed. These algorithms are based on the solution of a set of linear programming problems. Numerical examples illustrate the model.

Computation of GPS continuity with consideration of progress of time

AbstractThe international civil aviation organization (ICAO) has defined the international standard for the global navigation satellite system (GNSS) based on GPS for aviation use. Navigation systems for aviation must ensure not only the specific positioning accuracy but also the required reliability performance. Continuity is one of the measures of system reliability, and is defined as the probability that the system operates without nonscheduled interruptions over a certain period of time. We have already proposed a method of computing the continuity of GPS for the approach and landing flight phase. However, the method cannot be applied to flight phases such as enroute or terminal airspace because of the longer periods for such phases, for example 1 hour, over which the continuity requirements are defined. This paper describes a method of computing continuity with consideration of the progress of time, taking into account the movement of the aircraft relative to navigation satellites. Some computation examples are also presented. © 2002 Wiley Periodicals, Inc. Electron Comm Jpn Pt 1, 86(3): 26–34, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecja.10044

Reliability Measure Based on Average Loss of Capacity

We present an effective measure of system reliability based on average loss of call capacity that is appropriate for telecommunication hardware. We are led to consider a system consisting of units with many states with appropriately chosen performance effectiveness indices, while all atomic units are binary. In this respect, this effective measure of partial system availability is a variant of customer‐centered reliability methodology. We also identify the importance of a new structure called a ‘pool’ that behaves as a hybrid of series and parallel configurations. We present an algorithm for approximately calculating partial system unavailability, which solves the system decomposition problem for arbitrarily complex highly reliable systems made of hierarchically arranged k‐out‐of‐n sub‐structures. The algorithm agrees with our intuition for important special cases and has been programmed into an object oriented software tool. This method has been successfully used for the reliability analysis of GlobalstarTM gateways.

Estimation of raw sewage discharge resulting from sewer network failures

The raw sewage volume potentially discharged from a sewer network to the environment arising from its component failures is proposed as a measure of overall system reliability. This paper presents a simple method for quickly and properly calculating this volume. The basis for this method is a representation of the sewer network by a combination of Y-like fragments named here as structure-forming elements. Each such element is formally substituted by a fictitious equivalent sewer with a failure rate leading to the same output for the same input. A sequential application of this approach reduces the problem of estimating the discharged sewage volume to elementary subproblems for which the solution is simple. Examples are used to demonstrate the possibilities of this method.

Estimation of boundary points for continuum-state system reliability measures

Abstract A continuum-state system is considered, in which the performance levels of the system and its components range from perfect functionality to complete failure, allowing any intermediate state in the arbitrary interval. A number of recent papers on general continuum-state system reliability are briefly reviewed. A new approach based on the universal generating function technique is suggested for estimating boundary points of several reliability measures for such systems. It is shown, how the continuum-state system can be approached by using a finite multi-state system and how the bounds for the reliability measures may be found. The suggested procedure for estimating boundary points enables the engineer to base only on a representation of an ordinary system logic diagram. Using formal procedures, one can get upper and lower bounds for the entire continuum-state system reliability measures with preliminary specified accuracy. A numerical example for the suggested approach is presented.

Estimating reliability measures for highly-dependable Markov systems, using balanced likelihood ratios

Over the past several years, importance sampling in conjunction with regenerative simulation has been presented as a promising method for estimating reliability measures in highly dependable Markov systems. Existing methods fail to provide benefits over crude Monte Carlo for analyzing systems that contain important component-redundancies. This paper presents refined importance-sampling techniques that are also based on the regenerative technique. The new methods use an importance-sampling plan that dynamically adjusts the transition probabilities of the embedded Markov chain by attempting to cancel terms of the likelihood ratio within each cycle. Additional improvements are induced by concentrating on events affecting the size of minimum system cuts. These methods have solid theoretical properties and work well in practice, as illustrated by several examples.

Imprecise Reliability of General Structures

This paper discusses the important aspects of the reliability of systems with an imprecise general model of the structure function. It is assumed that the information about reliability behavior of components is restricted by the mean levels of component performance. In this case the classical reliability theory cannot provide a way for analyzing the reliability of systems. The theory of imprecise probabilities may be a basis in developing a general reliability theory which allows us to solve such problems. The basic tool for computing new reliability measures is the natural extension which can be regarded as a linear optimization problem. However, the linear programming computations will become impracticable when the number of components in the system is large. Therefore, the main aim of this paper is to obtain explicit expressions for computing the system reliability measures. We analyze the reliability of general structures and typical systems. The numerical examples illustrate the usefulness of the presented approach to reliability analyzing.

Reliability measures for two-unit systems with a dependent structure for failure and repair times

This paper deals with reliability measures for two-unit systems with a repair facility assuming that the failure times and the repair time follow a trivariate exponential distribution of Marshall and Olkin, J. Amer. Statist. Assoc., 1967, 62, 30–44. The case where the system down-time is observed, is also discussed. The system reliability and system mean-time before failure are evaluated for standby and parallel systems. When the down-time is observed the system availability, steady-state availability and the system mean down-time are evaluated for standby, parallel and series systems.

Entropy-based reliability analysis for intelligent machines

A new metric for performance assessment of intelligent machines has been developed. The method fuses concepts from the Theory of Intelligent Machines proposed by Saridis (1988) with traditional reliability analysis in the development of a measure which reflects both the uncertainty inherent in the intelligent machine and the uncertainty allowed by the task description. The metric is entropy based, and is shown to be analogous to a measure of system reliability.

MTBF as a System Reliability Measure

MTBF as a System Reliability Measure

Availability and frequency measures of a non-identical two component system in the presence of common cause shock failures

This paper discusses the presence of non-lethal common cause shock failures (NCS failures) in system reliability analysis. The system reliability measures availability ( A +( t)) and frequency of encountering the different states, is developed for a non-identical two component repairable system which is affected by NCS failures in addition to individual failures. Numerical illustrations are included in this paper.

A Bayesian Estimation of Reliability Measures of Stepwise Exponential Distribution System

This paper presents an analysis method for reliability measures of a system with step changes in failure and repair rates. Both failure and repair time have exponential functions of time. Such a system is called a stepwise exponential distribution system. This kind of failure process can take place in various kinds of equipment. This paper deals with the system having components in a series arrangement. Bayesian statistics are used in defining prior and posterior probability density functions of failure and repair rates. These functions provide information for the estimation of several reliability measures: (1) failure and repair rates, (2) mean time to failure, (3) mean time to repair, (4) reliability function and (5) availability. A sample problem is given to illustrate the methodology. Bayesian estimation of the stepwise exponential distribution model is useful in the planning predictive maintenance of equipment.

A Software Tool for Fault-Tolerant Systems in the Operational Phase

A software tool for predicting reliability and safety measures for computer or dynamical systems in the operational phase is presented. The considered models are markovian or semi-markovian. The background material which allows such predictions is based on new filtering formulas.

Analytical-statistical estimates for some reliability and efficiency measures of semi-Markov systems

A general approach is proposed to determination of analytical-statistical estimates of the main reliability and efficiency characteristics of high-reliability semi-Markov systems. The proposed approach substantially accelerates the simulation process in many applications.