ASQ - Electronics and Communications Division

Reliability Growth and the Caveats of Averaging: a Centaur Case Study

Abstract: 2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must first be obtained from the IEEE.

Spacecraft reliability modeling is plagued by data scarcity and lack of data applicability. Systems tend to be one-of-a- kind, and observed failures tend to be the result of systemic defects or human errors, instead of component failures. The result is too often a gap between two extreme estimating approaches: probabilistic risk assessments (PRA) that are component-based lead to optimistic estimates by ignoring system-level failure modes; while history-based failure frequencies can lead to pessimistic estimates by neglecting non-homogeneity (between vehicles and vehicle configurations), reliability growth, and improvements in design. The problem of non-homogeneity is often considered solved once a system has a sufficiently long history. But in reality, rarely can tens of launches be considered samples of the same probability distribution. Launch vehicles undergo design changes in their history; more accurate estimates of reliability need to account for the risk introduced by design changes and for two types of reliability growth: growth of a given system via systematic tracking, assessing, and correction of the causes of failure uncovered in flights; and general technological or knowledge growth over subsequent generations of the system.

Keywords: Failure Rate - Product Reliability - RAMS 2011 Proceedings - Reliability Analysis/Prediction/Estimation

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