ESTIMATION OF RELIABILITY OF A SYSTEM BY MONTE CARLO SIMULATION

Abstract

The basis of the concept of reliability is that a given component has a certain stress —resisting capacity. If the stress induced by the operating conditions exceeds this capacity , failure results occur. Most of the obtained result in this area are based upon analytical modelling of stress and strength , using various probability distributions function, and then trying to find an exact expression for system reliability, which can be very difficult to obtain sometimes. The approach used in this dissertation uses simulation techniques to repeatedly generate stress and strength of a system by the computer, using a random number generator and methods such as inverse transformation technique. The advantage of this approach is that it can be used for any stress -- strength distribution functions, such as normal distribution, gamma distribution, exponential distribution, log normal distribution, and weibull distribution. In addition to this, failure intensity and mean time between failure of a system has evaluated by using monte carlo simulation technique. Failure intensity and mean time between failure are very useful tools for the understanding the reliability. The result of reliability, mean time between failure, for percent failed at given time, given time, beta(shape factor), time of interest, mean life, has also calculated by weibull distribution. The result show the viability of the monte carlo simulation approach.