Prognostics and Health Management

7Prognostic Enabling: Selection, Evaluation, and Other Considerations

7.1 Introduction to Prognostic Enabling

As you have already learned, a key objective of deploying a prognostic‐enabled system is to monitor prognostic targets to provide advanced warning of failures in support of condition‐based maintenance (CBM). There are criteria associated with, for example, equipment availability and other metrics, test coverage, and confidence levels. To meet the criteria, the various sensing, signal‐processing, and computational (algorithms) routines in a prognostics and health management/monitoring (PHM)¹ system need to be factored into the entire design. CBM methods and approaches – especially those using condition‐based data (CBD) signatures that are ultimately transformed into functional failure signature (FFS) data that is processed by a very good prognostic information program – provide significant advantages over (i) a system based on statistical or other methods applicable to populations rather than a specific instantiation of a population and (ii) a system based on using CBD to detect damage without prognosing when such damage will result in the system no longer operating within specifications.

7.1.1 Review of Chapter 6

Chapter 6 presented a design of an exemplary prototype of a PHM system that prognostic‐enabled multiple instantiations of systems and prognostic targets with excellent results (see Table 7.1).

Table 7.1 Performance measurements and metrics.

Prognostic ...