Three numbers — operating hours, failure count, and total downtime — are all it takes to know how reliable an asset is and how fast your team recovers when it breaks. Enter yours to get MTBF, MTTR, and availability instantly.
Availability
98.3 %
Good
At 98.3% availability, solid, with room to tighten up repeat failures.
RunTight is free for teams up to 25 · How to measure MTTR properly
MTBF (mean time between failures) measures reliability: on average, how long a repairable asset runs before it breaks down. A rising MTBF means your preventive maintenance is catching problems before they become failures. MTTR (mean time to repair) measures maintainability: once something breaks, how long it takes your team to get it running again — from detection through diagnosis, parts, repair, and testing. Together they feed the metric operations actually cares about: availability, the percentage of scheduled time the asset is actually able to run.
This calculator uses the standard definitions for a repairable asset over a measurement period:
Only count unplanned failures and their downtime — planned PM stops are scheduled time out of service, not failures, and mixing them in makes both metrics meaningless. If an asset had no failures in the period, MTBF is undefined (not infinite); extend the window until it includes at least a few failures.
Say a packaging line is scheduled to run 720 hours in a month (24/7 operation). It breaks down 3 times, and those breakdowns cost 12 hours of downtime in total. MTBF is (720 − 12) ÷ 3 = 236 hours — roughly ten days of running time between failures. MTTR is 12 ÷ 3 = 4 hours per repair. Availability is 236 ÷ (236 + 4) × 100 = 98.3%. That is a solid result, but the interesting part is the trend: if the same line shows MTBF falling month over month, something is degrading, even while availability still looks fine.
Be wary of anyone quoting precise industry-average MTBF figures — reliability varies enormously by asset type, age, duty cycle, and operating environment, and a “good” MTBF for a 20-year-old compressor is very different from one for a new conveyor. Some conservative rules of thumb do hold across contexts: availability of 99% or better is generally excellent for equipment in continuous operation, 95–99% is a healthy range for most small maintenance teams, and anything below 95% usually means unplanned downtime is materially disrupting the schedule and deserves a root-cause look. The most useful benchmark is always your own history: measure per asset, compare period over period, and investigate the trend rather than chasing a universal target. Our guide to maintenance KPI tracking for small teams covers which handful of metrics are worth the effort.
MTBF rises when failures stop happening, and that is a preventive-maintenance problem. Put every asset on a PM schedule matched to its duty cycle, and actually complete those PMs on time — a schedule nobody follows changes nothing. Log every failure with a cause, then look for repeat offenders: a handful of assets usually generate most breakdowns, and fixing the underlying issue (misalignment, contamination, worn components replaced too late) beats repairing the same symptom monthly. Operator basics like cleaning and lubrication rounds are cheap and move the needle more than most teams expect.
MTTR falls when repairs start faster and finish sooner. Most MTTR is not wrench time — it is waiting: to notice the failure, to find the manual, to locate the part. Faster failure reporting, asset histories and procedures available at the machine, and stocked critical spares each cut that waiting time directly. Timing the clock consistently matters too — measure from detection to restart, every time, or your trend line is noise. For a practical walkthrough of measuring and reducing repair time on a small team, see how to calculate MTTR for small maintenance teams.
There is no universal number — a good MTBF depends on the asset, its duty cycle, and how critical it is. The practical answer is that a good MTBF is one that is longer than your PM interval and trending upward. Track it per asset over several periods: if MTBF is rising, your maintenance program is working; if it is falling, failures are outpacing your preventive work.
MTTR (mean time to repair) is total unplanned downtime divided by the number of repairs in the same period. If three failures cost you 12 hours of downtime in a month, MTTR is 12 ÷ 3 = 4 hours. Count the full clock from failure detection to the asset running again — diagnosis, waiting on parts, the repair itself, and testing — not just wrench time.
MTBF (mean time between failures) applies to repairable assets — pumps, conveyors, HVAC units — and measures the average operating time between one failure and the next. MTTF (mean time to failure) applies to non-repairable items that get replaced rather than fixed, like light bulbs, bearings, or fuses, and measures average lifespan until the failure that ends the item's life.
RunTight is free for up to 25 users — the full CMMS, no credit card required. Pro adds advanced analytics, including automatic MTBF and MTTR reports per asset, for $49/month.
Related: CMMS ROI Calculator · RunTight pricing