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Prognostics and health management methods can provide advance warning of failure; reduce the life cycle cost of a product by decreasing inspection costs, downtime, and inventory; and assist in the design and logistical support of fielded and future electronic products. Traditional prognostic methods, such as data-driven methods and physics of failure methods have some limitations. This paper presents a fusion prognostics method, which fuses data-driven methods and physics of failure methods to predict the remaining useful life of electronic products. This method integrates the advantage and overcome the limitations of the data-driven methods and the physics of failure methods to provide better predictions.
Cheng et al. (Sat,) studied this question.