Trend analysis and prediction represents a processing capability that is added to the system. Most often, it runs on-board and supplies enough information to remediate before a critical failure. It can also be used for condition-based maintenance (CBM) and a host of other situations where detection prior to actual failure provides cost and safety benefits.Accounting for this capability in the design itself is done by acknowledging the percentage of time that failures can be detected prior to their failure. That is, to what degree can insipient failures be recognized.
In eXpress, there are two approaches to adding this knowledge. First, let's consider the case where only functions exist, and there are no failure modes on the component of interest. In this case, eXpress' hybrid diagnostic model provides a quick and simple solution. Add a failure mode for each prognostic capability with a rate equal to the percentage of time that the insipient failure is identified before actual failure.
In the second case, both functions and failure modes already exist. Adding the prognostic prediction in this case means breaking existing failure modes into two or more pieces. One piece represents the percentage of time that the failure occurs suddenly without prior detection through trending, while other pieces represent those percentages of time that a trend is identified first.
Next, we will discuss the implications of these changes to the existing testing and diagnostic knowledge.