A Model-Based Approach for Reliability Prediction

Abstract: When developing products, reliability is an important factor that has to be considered. For safety critical systems it is important to know the probability that an item will perform a required function without failure under stated conditions for a stated period of time. The main goal of a reliability prediction analysis is to predict the rate at which the product of a system will fail. To perform this prediction there are a number of methodologies available. This Master Thesis proposes a model-based approach for reliability prediction calculations based on the physics of failure and supported by analysis of test-data field returns and physical models provided by the FIDES methodology. FIDES based reliability models have been integrated into a model-based diagnosis environment for seamless integration with other safety assessment analysis. The model-based diagnosis environment used in this thesis is model-based reasoner RODON developed by Uptime Solutions AB. Components that uses the FIDES methodology have been developed in RODON, where components can be combined to systems by drag and drop method. Usage profiles that are defined according to the FIDES methodology in RODON are not system specific, which makes them reusable in other systems. The developed library of components and usage profiles makes it easy to model complex systems and perform reliability predictions according to the FIDES methodology.