EMS Grand Rapids posted this simple, but powerful, definition. With it, you can simply estimate your expected cost due to failure for a machine over its lifetime: With reliability (as defined) = R,
cost of failure = (1 - R) x (cost to repair/replace + cost of downtime x time to repair/replace)*
You can compare this expected cost with the up-front and lifetime costs (if any)** of mitigating measures and make an informed decision on whether to take those measures. For example, an AEGIS ring for a motor on a drive might cost a few hundred dollars. How does that compare to the expected cost of motor bearing failure due to electrical damage?
*This equation assumes the equipment fails at most once over its lifetime... not always the case! So it is a lower limit. At R = 0.95, there is ~ 0.1% risk of repeated failures; at R = 0.9, the risk is over 1%. To continue the example of motors on drives, estimates of failure rates due to electrical bearing damage range from 20% up to 50%, giving R = 0.8 at most, even neglecting other failure modes.
**To be more rigorous, you would also calculate R with the mitigating measures in place, and add the expected cost of failure with mitigation to the up-front and lifetime costs of mitigation. The lifetime costs can include maintenance to the mitigation (like adjusting carbon brushes) and increased power consumption (due, for example, to voltage drop caused by VFD output filters).
Reliability is the probability an item will function correctly when needed, for the period required, in the specified environment.
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