MTBF – Mean Time Between Failure

By: Diane Shired, CTM

Meaning of MTBF – "Mean Time Between Failure”, is the average frequency with which a product fails, the average time between failure or the length of time a component or computer hardware is expected to work without failure. It is also an indicator of system reliability that is calculated from known failure rates of various system components. MTBF measure how reliable a product is, it indicates the failure rate of computer hardware and server components and is usually given in units of hours. MTBF is not the correct tool for all applications, but is a very useful tool for measurements of reliability.

The product is more reliable the higher the MTBF rating. The MTBF is determined by dividing the number of failures by the hours the object is under manufacturer’s observation. If a product has a MTBF rating of 45000 then the system would not have a failure for approximately 5 years. MTBF is not related to life expectancy or the operating life of the product. A failure assumes that the product can resume normal operation or that the product can be repaired. MTBF has nothing to do with product lifetime. What it does, it can help to quantify the suitability of a system or component for a potential application.

Other Related Definitions:

“Mean Time Between Failure is a reliability term used loosely throughout many industries and has become widely abused in some. Over the years the original meaning of this term has been altered which has led to confusion and cynicism. MTBF is largely based on assumptions and definition of failure and attention to these details are paramount to proper interpretation. This paper explains the underlying complexities and misconceptions of MTBF and the methods available for estimating it.” [Silicon.com - Publisher's Description]

“Mean Time Between Failure (MTBF) is a much-used management metric in IT both for discrete components as well as overall systems.

For simplicity, let's define MTBF as the average time between failures. It's either based on historical data or estimated by vendors and is used as a benchmark for reliability. Organizations trending MTBF over time can readily see devices that are failing above average and take appropriate action.

Where MTBF breaks down is when management puts too much faith in unproven MTBF estimates and uses them to justify inordinately massive amounts of capital investment on complex systems. This may seem to be a bold statement and therefore requires some explanation.

If we assume that there are 8,760 hours per year (365 days x 24 hours per day) then we can divide MTBF claims from vendors and look at how long the system will run in years. If we buy a system, or component, with a rating of 30,000 MTBF, then we might assume that on average, the system would run 3.42 years without a failure. Granted, there are always statistical variations around the average, but 3.42 years doesn't seem bad at all, does it?” [InternetNews.com - By George Spafford]

Related Links:

Analog Engineering Solutions - Reliability Prediction - Parts Count MTBF
shsu.edu - Mean Time Between Failure
News, references and more on Engineeringtalk - Mean Time Between Failure

Technical Resources:

Mean Time Between Failures (MTBF)
The PC Guide

Products and Solutions:

The Mean Time Between Failure for Token Express™ MCA Adapters Using STP cabling:
Reliability Prediction and Testing
Planning for High Availability: Attempt to Eliminate Downtime

Blogs, News, Feeds, Discussion Lists:

Mean time between failure in Windows XP
A Guide to Measuring Reliability - Mean Time Between Failure (MTBF)
Model Dynamics
Relying on leadership
Desktop RAID: Oversold?

Books About:

The Statistical Analysis of Failure Time Data (Wiley Series in Probability and Statistics) - by John D. Kalbfleisch, Ross L. Prentice
R&M, productivity key spindle developments: high speed, yes, but longer MTBF. (Spindles).(reliability and maintainability beats Mean Time Between Failure)- by Jim Lorincz

See Also:

Other MTBF Related Resources

 

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