Abstract :
Reliability is the ability of a product or system to perform as intended (i.e., without failure and within specified performance limits) for a specified time, in its life-cycle environment. Commonly-used electronics reliability prediction methods (e.g. Mil-HDBK-217, 217-PLUS, PRISM, Telcordia, FIDES) based on handbook methods have been shown to be misleading and provide erroneous life predictions, a fact that led the U. S. military to abandon their electronics reliability prediction methods. The use of stress and damage models permits a far superior accounting of the reliability and the physics-of-failure, however sufficient knowledge of the actual operating and environmental application conditions of the product are still required. This paper presents a physics-of-failure based prognostics and health management approach for effective reliability prediction. The procedure includes failure modes, mechanisms, and effects analysis, data reduction and feature extraction from the life cycle loads, damage accumulation, and assessment of uncertainty.
Keywords :
data reduction; electronic products; failure analysis; feature extraction; reliability; U. S. military; damage accumulation; damage models; data reduction; electronic products reliability; electronics reliability prediction methods; environmental application conditions; failure modes; feature extraction; health management approach; life cycle loads; physics-of-failure based prognostics; uncertainty assessment; Failure analysis; Management training; Military standards; Power system modeling; Prediction methods; Predictive models; Prognostics and health management; Reliability engineering; Space technology; Stress;
