An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples, volume 1

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design or failure prediction are used in this methodology. The PFA methodology can be applied at any time in the design, development, or operational phases of a program to quantitatively estimate failure risk based on the information available at the time failure risk is assessed. Sensitivity analyses conducted as a part of PFA can be used to evaluate and rank such alternative measures to control risk as design changes, testing, or inspections, thereby enabling limited program resources to be allocated more effectively. PFA is generally applicable to failure modes that can be characterized by analytical or empirical models of failure phenomena and is especially useful when models or information used in analysis are uncertain or approximate. Such failure modes include, but are not limited to, fatigue, flaw propagation, rupture, degradation and wear, and malfunction of mechanical or electrical systems. It is often not feasible to acquire enough test experience to establish high reliability at high confidence for spaceflight systems. Moreover, the results of conventionally performed engineering analyses of failure modes can be subject to serious misinterpretation when uncertain or approximate information is used to establish analysis parameters and calibrate the accuracy of analysis models. Under these conditions, a quantitative evaluation of failure risk based on the information available from both test or flight experience and engineering analysis is needed to make effective risk management decisions.