Failure rates, in the simplest form, are S(time in use)/S(number of failures) or the reciprocal of mean times to/between failure. For more sophisticated failure data bases such as Weibull data bases the failure rates can be disclosed without giving away proprietary data such as the shape factors, beta, which tell the failure mode for the equipment.
Why: Simple failure rates are a precursor of maintenance events and production interruptions that will occur into the future which drive up costs and cause chaos.
When: Failure rates derive from the history of operation or from well known data sources such as OREADA, IEEE 500, IEEE 493, EPRI, and other sources listed in reading lists for reliability including Weibull databases.
Where: The failure rates are used as an awareness criteria for the average person just as you used automobile fuel consumption rates for understanding the health of your automobile as well as anticipating your weekly/monthly/annual out-of-pocket expenditures for gasoline or diesel fuel. The failure rates drive the maintenance interventions, spare parts, and maintenance cost for the Maintenance Department. Similarly they predict the interruptions to the process and lead to misses on promised deliveries and result in negative variances for production costs. In sort, failure rates are precursors for the misery expected for the organization.
These definitions are written by H. Paul Barringer and are also posted on his web site at www.barringer1.com
Comments (1)
Saying that failure rate is (time in use)/(number of failures) is incorrect. It will give us hour/failure whereas the failure rate is failure per hour(month, year etc.)
What is "mean times to/between failures" is very unclear. This is probably an attemp to say that failure rate is the reciprocal of mean time to failure.
1) Posted 5:36 pm, 26 August 2010 by Dmitry