Availability = Run Time ÷ Planned Production Time. If a machine runs for 9 hours and 15 minutes out of an 11-hour scheduled shift, availability is about 84%. It's the first of the three factors in OEE (overall equipment effectiveness) — and the one maintenance has the most direct control over.
The formula and a first worked example
Availability (%) = Run Time ÷ Planned Production Time × 100
Run time is planned production time minus downtime. Planned production time is the time the line was scheduled to run — it excludes breaks, shift changes, and time nothing was scheduled at all.
Worked example (illustrative — substitute your own line's data)
A CNC cell is scheduled for an 11-hour shift. During that shift, it loses 105 minutes to an unplanned tooling failure and 35 minutes to a scheduled changeover.
| Element | Value |
|---|---|
| Planned production time | 660 min |
| Unplanned downtime | 105 min |
| Planned downtime (changeover) | 35 min |
| Run time (unplanned-only) | 660 − 105 = 555 min |
| Run time (both excluded) | 660 − 140 = 520 min |
Counting only unplanned downtime: 555 ÷ 660 × 100 ≈ 84.1% availability. Counting both planned and unplanned downtime: 520 ÷ 660 × 100 ≈ 78.8% availability.
Which one is correct depends on what you're measuring — see the mistakes section below. Prefer to skip the arithmetic? Our availability calculator does this math for you — enter run time and planned production time for an instant percentage.
OA vs OEE — what's the difference?
These get used interchangeably on a plant floor and they aren't the same number.
OA (Overall Availability, sometimes just "Availability") is a single-factor measurement: what fraction of scheduled time was the machine actually running. It answers one question — was the equipment available?
OEE (Overall Equipment Effectiveness) multiplies three factors together: Availability × Performance × Quality. Performance asks whether the machine ran at full speed while it was available. Quality asks whether the parts it made were good. A machine can have 95% availability and still have poor OEE if it runs at 70% of rated speed or produces 10% scrap.
The practical difference: availability alone tells you the equipment was there to produce. OEE tells you how much good output actually came out of the time it had. A plant chasing an availability number without knowing performance and quality is missing two-thirds of the picture — see our full OEE guide for how the three factors combine.
Common mistakes calculating availability
Forgetting to exclude planned downtime consistently. If one week you count changeovers against availability and the next week you don't, the trend line is meaningless. Pick one definition and use it every time — the worked example above shows both are legitimate, but only if applied consistently.
Conflating availability with utilization. Utilization asks what fraction of total calendar time (24/7) the machine ran — a different denominator than planned production time. A machine that's 95% available during its scheduled shifts can have low utilization if it's only scheduled for one shift a day. These answer different questions; using them interchangeably confuses whoever's reading the report.
Treating a single snapshot as a trend. One shift's 80% availability tells you almost nothing on its own. The trend over weeks — is it climbing, flat, or declining — is where the actionable signal lives.
Not separating availability loss by cause. An 80% availability number that mixes a single 2-hour breakdown with ten 12-minute micro-stops looks the same on paper but needs two completely different fixes. Break the loss down by cause before deciding what to act on.
Multi-shift availability
Availability compounds across shifts the same way it does within one — sum the run time and planned time across all shifts in the period, then divide.
Worked example (illustrative)
A line runs three 8-hour shifts, 6 days a week — 144 scheduled hours. Over that week: Shift A loses 2 hours to a breakdown, Shift B loses 1.5 hours to two smaller stops, Shift C runs clean.
| Shift | Planned hours | Downtime | Run time |
|---|---|---|---|
| A | 48 | 2.0 | 46.0 |
| B | 48 | 1.5 | 46.5 |
| C | 48 | 0 | 48.0 |
| Total | 144 | 3.5 | 140.5 |
Weekly availability: 140.5 ÷ 144 × 100 ≈ 97.6%.
A single-shift snapshot (say, Shift A alone at 46 ÷ 48 = 95.8%) would have looked worse than the week actually was — which is why a multi-shift or weekly view, not a single shift, is the right level to report at.
What actually moves the availability number
Availability is the OEE factor maintenance has the most direct lever over — performance and quality usually need engineering or process changes, but availability loss is mostly breakdown maintenance and PM slippage, both squarely inside maintenance's control. A PM program that actually runs on schedule, root-cause capture that stops the same failure from repeating, and MTBF tracking that surfaces a machine's reliability trend before it becomes a stoppage — these are the concrete actions that move availability, covered in our maintenance KPIs guide.
The mistake I see most often on the floor is what teams put in the denominator — they don't consistently strip out unplanned downtime, or they lump setup and changeover time in with it, so the number moves for reasons that have nothing to do with actual equipment performance. Pick one definition and hold it every reporting period; which convention you pick matters far less than never switching mid-trend.
How MachDatum tracks the inputs to availability
MachDatum doesn't compute OEE — Performance and Quality data come from the machine or production system, not maintenance records. What it does compute automatically from closed work orders is the availability input: downtime hours by asset, MTTR, and MTBF, updated every time a repair work order closes.
Where MachDatum fits: downtime by asset, MTTR, and MTBF update automatically from work-order history — no spreadsheet, no manual re-entry. If availability loss is being driven by breakdowns and PM slippage — the most common pattern — that's the input this data feeds directly. We're onboarding our first group of manufacturing teams right now — see how it works at machdatum.com.
