Complex system reliability estimation methodology in the absence of failure data

Abstract

This paper presents a comprehensive system reliability estimation methodology for cases when failure data are unavailable, at least initially. In this methodology, the laws of physics and thermal fundamentals are used to establish a mathematical model that relates the influential input operating characteristics, such as material properties and geometry, to system performance measures. Probability distributions for each influential operating characteristic, identified from the available manufacturing data, information found in instruction manuals and related technical journals, and expert knowledge, are used to simulate the system behavior with Monte Carlo simulation. An initial reliability estimate is obtained by comparing the simulated system performance with the permissible system performance. Fuzzy logic is used to incorporate the impact of environmental factors on the performance of the simulated system performance and hence the system reliability. Finally, with the use of Bayesian analysis, initial system reliability is updated to take into account the effect of environmental factors.The proposed methodology is applied to estimate the reliability of the hazardous gas detection system used in aerospace shuttles for the timely detection of explosive gases.

An effective sensitivity analysis methodology for the reliability‐based structural optimization design to high temperature components

“…There are a number of approaches to obtain the failure probability P f of structural components, among which the Monte Carlo Simulation (MCS) is particularly applicable when failure data are not available and exact mathematical equations can become quite involved 16 . In particular, the major disadvantage of MCS will become more evident when analysis is required of the sensitivity of P f to the statistical parameters describing the probability distributions of random variables.…”

Mathematical Modeling and Availability Analysis of Leaf Spring Manufacturing Plant

“…Jain et al (2004) dealt with the degraded machine repair problem for the finite population Bernoulli feedback model. Yadav et al (2008) developed a technique in the absence of data concerning failures. Agarwal and Bansal (2009) studied the head of line repair strategy to evaluate the reliability of a dynamic standby redundancy system with evolving environmental conditions.…”

The Performance Assessment of a MANET using WUGF

“…The reliability analysis of various networks becomes a major concern for several decades. There are many approaches for executing network reliability (Levitin, 2001;Yadav et al, 2008;Lei et al, 2010). Chaturvedi and Misra (2002) have proposed a hybrid method to evaluate the reliability of complex networks.…”