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MTBF, MTTR & Availability Calculator

Mean time between failures, mean time to repair and inherent availability from operating hours and failure counts — failure rate, reliability over a mission time, expected failures per year and the “nines” of uptime.

Total operating time observed
Number of identical units observed
Failures in that period (all units)
Total repair / restore time (all failures)
Mission time for the reliability estimate
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How it works

MTBF = total operating hours ÷ failures; MTTR = total repair hours ÷ failures; availability = MTBF ÷ (MTBF + MTTR); λ = 1/MTBF; reliability R(t) = e^(−λt)

MTBF is the average operating time between failures of a repairable item, pooled across all units observed; MTTR is the average time to restore it. Their ratio gives inherent availability — the long-run share of time the item is up — which is why a component with a short MTBF can still deliver high availability if it is fixed quickly, and why redundancy and spares strategy focus on MTTR as much as on reliability. Assuming a constant failure rate (the flat part of the bathtub curve), reliability over a mission time falls exponentially, so an item with a 3,650-hour MTBF has only an 82% chance of surviving a 720-hour month; MTBF is not a lifetime. Real fleets show infant mortality and wear-out, so treat these figures as steady-state estimates and refresh them as data accumulates.

Worked example

Ten units run a year (87,600 unit-hours) with 24 failures and 96 repair hours: MTBF 3,650 h, MTTR 4 h, availability 99.89% (about 9.6 h down per unit per year). Reliability over a 720-hour month is 82%; expect about 24 failures a year across the fleet.

Frequently asked questions

MTBF vs MTTF?

MTTF (mean time to failure) is for non-repairable items — how long until the first and only failure. MTBF applies to items that are repaired and returned to service.

Does MTTR include waiting for parts?

Inherent availability uses active repair time only; operational availability adds logistics and administrative delay, which is usually what the business actually experiences.

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Operations planning estimate based on the figures entered; validate against measured shop-floor data before changing staffing, equipment or customer commitments.