A practical approach to system reliability growth modeling and improvement

Abstract

In a product development process, to develop appropriate design validation and verification program for reliability assessment, one has to understand the functional behavior of the system, role of components in achieving required functions and failure modes if component/sub-system fails to perform required function. In this paper, the authors propose a simple and practical two-stage approach of system reliability growth modeling considering components, functions, and failure modes. The consideration of these three dimensions will help in uncovering the weak spots in design responsible for low system reliability. The proposed method assumes Weibull distribution as failure time distribution and reliability model is based on the Bayesian framework incorporating even fuzzy information. The fuzzy logic model that has been developed for this purpose is used to quantify the engineering judgment or fuzzy information of reliability improvement attributed to design changes or corrective actions. Uncertainty in data/information at component levels propagates to system level reliability and makes system reliability prediction highly unreliable. The paper suggests a variance reduction strategy to give more accurate system reliability predictions.