Prognostics and Health Management of Electronics

8 Uncertainty Representation, Quantification, and Management in Prognostics

Shankar Sankararaman

One Concern, Palo Alto, CA, USA

This chapter analyzes the significance, interpretation, quantification, and management of uncertainty in prognostics, with an emphasis on predicting the remaining useful life (RUL) of engineering systems and components. Prognostics deals with predicting the future behavior of engineering systems and is affected by various sources of uncertainty. In order to facilitate meaningful prognostics‐based decision‐making, it is important to analyze how these sources of uncertainty affect prognostics, and thereby, compute the joint effect of these individual sources of uncertainty on the overall uncertainty in the RUL prediction. However, several of the state‐of‐the‐art industrial techniques do not consider a systematic approach to the treatment of uncertainty. This chapter explains the paramount importance of uncertainty interpretation, quantification, and management in prognostics, focusing both on testing‐based life prediction and condition‐based prognostics. In particular, the suitability of classical (frequentist) and subjective (Bayesian) approaches to uncertainty is discussed in detail. Computational methods for uncertainty quantification and management are explained and illustrated using numerical examples. Finally, several challenges involved in the application of these methods to practical applications are also discussed.

8.1 Introduction ...