Reliability Modeling of Complex Components Using Simulation

This paper is a continuation of papers presented at the 13^th and 15^th Probabilistic Safety Assessment and Management Conferences [1, 2]. The previous work presented discussions of modeling failure modes of complex components and the effects of censor bias. The first paper demonstrated how the typical method of treating failure modes as exponential gives optimistic predictions when predicting how improvements to subcomponents will perform. Instead of relying on traditional analytical methods, a more accurate approach is to model the failure modes as a race in time. Unfortunately, this does not give a closed-form solution and requires a more advanced solution. A simulation with pre-defined component attributes demonstrated the optimistic nature of classical techniques. Unfortunately for complex systems, the simulation routine may become very complex and difficult to implement. The second paper demonstrated the effect of censor bias when dealing with large amounts of success-only testing, and the difference between treating data as "missing" instead of censored. In the quest for closed-form solutions and simplicity, the world of reliability engineering relies on the exponential distribution. In most cases, it makes the solution closed-form and easy to solve. However, simple models may lead to incorrect results when modeling even something as simple as modeling to the failure mode or component/subassembly level. An excellent real-world example of using exponential distributions in this context is the typical automobile. No one expects a new car to have the same failure intensity as an older car. Obviously a more advanced approach is needed, and not just at the component level. This paper will use two approaches to analyze a simple system with components that have more than one failure mode. The first is a standard fault tree, and the second is a simulation. In both methods, various data assessment methods will be used to compare the results of both the data assessment method and the solution. A discussion of the results will follow.