Modeling Launch Vehicle Reliability Growth as Defect Elimination

Abstract

The historical success and failure record of launch vehicles clearly demonstrates the presence of reliability growth over successive launches. The reality of reliability growth is critical to decisions on ground and flight testing programs, and is a much greater driver of the expected number of failures over a campaign, than the best analysis of mature reliability can ever be. While mathematical models exist that match the reliability growth demonstrated by historical systems, the space industry is still lacking a practical method to develop forecasts of reliability growth for new systems, update those forecasts on the basis of early tests and flight results, and accurately estimate integrated campaign metrics over several launches. Modeling the failure probability as originating from potential “defects” in the system, each with a probability of trigger, a conditional probability of causing loss of mission, and a probability of detection and correction, provides a starting place to address this need. The method provides a model of reliability growth that is mathematically sound, matches historical results, is directly amenable to system engineering inputs, clearly identifies and quantifies the drivers of reliability growth, and provides a clear basis for uncertainty analysis and Bayesian updating.