Jie Gu and Michael Pecht
University of Maryland
College Park, MD 20742
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 lifecycle 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. physics-of-failure is an approach that utilizes knowledge of a product's life cycle loading and failure mechanisms to perform reliability modelling, design, and assessment. This method permits the assessment of the reliability of a system under its actual application conditions. It integrates sensor data with models that enable in-situ assessment of the deviation or degradation of a product from an expected normal operating condition (i.e., the system's "health") and the prediction of the future state of reliability. This paper presents a formal implementation procedure, which includes failure modes, mechanisms, and effects analysis, data reduction and feature extraction from the life cycle loads, damage accumulation, and assessment of uncertainty. Applications of physics-of-failure based prognostics and health management are discussed, including legacy systems, storage reliability, and new product development.
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