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Mean Time to Failure (MTTF): What It Measures, and How It Differs from MTBF
Mean time to failure, or MTTF, is the average life you get from a non-repairable item before it fails for good: a bearing, a bulb, a sensor you replace rather than fix. It is often confused with MTBF, but MTBF applies to repairable equipment that fails and is fixed again and again. The difference is whether you repair the item or replace it.
Why does MTTF matter?
Mean time to failure tells you how long a non-repairable part typically lasts, which is the basis for planning replacements and spare-parts stock before it fails in service. Get it wrong and you either replace good parts too early or run them to an unplanned breakdown. Used correctly, it feeds preventive maintenance planning and reliability decisions.
How is MTTF calculated?
It is an average across a population of items, not a guarantee for any single unit:
- Add up the total operating hours across the items you are studying.
- Divide by the number that failed in that time.
- The result is the average hours a unit runs before it fails.
- It describes the batch, so a 50,000-hour MTTF does not mean any individual part will last 50,000 hours.
How does MTTF differ from MTBF and MTTR?
It comes down to whether the item is repairable. MTTF is for items you replace, so there is one failure per item. MTBF is for equipment you repair, measuring the average uptime between failures across its life. MTTR, mean time to repair, is the other side: how long the fix takes once it does fail. Use MTTF for the replaceable part, MTBF for the machine it sits in.
MTTF vs MTBF vs MTTR at a glance
Three reliability metrics people blur together.
| Metric | Measures | Used for |
|---|---|---|
| MTTF | Average life before failure | Non-repairable items |
| MTBF | Average uptime between failures | Repairable equipment |
| MTTR | Average time to repair | How fast you recover |
Related Terms
- Preventive Maintenance (PM) – planned around expected life.
- Downtime – what a failure causes.
- Machine Availability – driven by failure and repair rates.
- Wear and Tear
