A Fast Algorithm for Reliability Evaluation
ABSTRACT An algorithm is developed to obtain a simplified reliability expression for a general network. All the success paths of the network are determined; then they are modified to be mutually disjoint. The reliability expression follows directly from the disjoint paths. The algorithm is easy and computationally economical. The reliability expression involves fewer terms and arithmetic operations than any of the existing methods. This is an advantage, considering the size of the system a reliability engineer normally handles and the frequency with which the expression is used for reliability studies.
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ABSTRACT: Since the traditional reliability analysis based on probability theory has been widely used in practical life, it suffers difficulties in system reliability with limited or insufficient statistical data. Thus the work of uncertain reliability researches in small sample or no-sample systems are given by many researchers. However in more general cases, uncertainty and randomness simultaneously appear in a system. For example, some elements have no samples while others have samples enough to determine probability distributions. In order to cater for this case, the reliability in uncertain and random system is considered in this paper. The definition to the reliability in a Boolean uncertain random system is given, and some theories is proved. Some special systems are also considered as examples, including series system, parallel system and k-out-of-n system. Since the reliability in the Boolean system requires the knowledge of structure function which is difficult to get in the complex systems, we will present a method to get the minimal paths by which we can get the structure function. simultaneously, the lower bound of the uncertain random reliability is estimated by the minimal paths. Finally, a simple example is designed to illustrate the definition and the theories.
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ABSTRACT: In the paper a number of various types of vessels' power plant steam system failures have been analyzed with regard to the general population they come from. For the purpose of the analysis the Kruskal – Wallis rank sum test and Kruskal – Wallis ANOVA rank test from the statistical packet STATISTICA 8.0 have been used. The analysis was based on the observations of the failure of marine power plants steam systems elements. Failures to the marine power plant systems of 10 ships owned by the Polish Steamship Company of Szczecin was the subject of a statistical data analysis. All the ships differed in respect to their place and time of construction as well as their technical parameters. The data on marine power plants failures was collected in similar conditions, that is, they were supplied by an engine crew member working in the marine power plant. The data on the failures of particular marine power plant systems was obtained accordingly to the test schedule [N, W, T], which means that N renewable objects were the subject of the test within the time T. Since the recovery time of the damaged system appeared negligibly short, when compared to the time of the test, it was assumed that consecutive recoveries overlap the failure moments. The statistical analysis dealt with moments of the particular systems' consecutive failures and the length of time intervals n t t t ≤ ≤ ≤ ... 2 1 n τ between the objects' consecutive failures.
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ABSTRACT: The articles of this volume will be reviewed individually.