Internal and external CBM variables

As maintenance or reliability engineers we need to discover what factors influence failure and failure probability. Which of those factors can we control, and which can we monitor for their predictive content. It will help to distinguish between External and Internal variables.

Definition:

External CBM variables such as loading, operator discretionary actions, shock, terrain, etc. contribute to the causes of failure.

Internal CBM variables such as vibration amplitude, dissolved metals and contaminants in the lubricating fluids reflect and might reveal  the state of failure mode progression. That is, some of the effects of failure.

• External variables  contribute to failure.
• Internal variables  influence failure probability.

We analyze both external and internal variables for CBM prediction and optimization in exactly the same way. Often external variables can contain greater predictive content than do internal variables. External variables such as operating regime, visual observations, cleanliness state, or the frequency of needed adjustments are relatively inexpensive and quick to acquire. Often “low tech” and less “glamorous” then internal variables, they tend to be ignored. External variables can include records of shock or overload conditions whose cumulative compilation may predict failure accurately even before the failure process has actually initiated. Internal variables depend on a failure to have already begun. Hence we might say that external variables can be more “proactive” than are internal variables.

Mathematically there is little difference between between the analysis of internal and external variables that precede failure or suspension events. Both can exert influence on failure probability. Hence, both are analyzed and modeled in EXAKT in the same way. Reliability engineers should be creative and open minded when selecting candidate variables for CBM optimization by considering their physical relationships to to the failure modes of interest.