Key takeaways
Unplanned downtime, also called unscheduled downtime, is time when a machine or line was supposed to produce but stopped for a reason nobody planned.
The defining feature is that the timing is imposed on you. You do not choose when it happens, how long it lasts or who is available to fix it.
Typical examples:
| Planned downtime | Unplanned downtime | |
|---|---|---|
| Timing | Chosen in advance | Imposed by a failure or a missing input |
| Examples | Changeovers, cleaning, scheduled maintenance, trials | Breakdowns, long jams, material shortages, quality holds |
| Preparation | People, parts and tools ready | Search for people, parts and information |
| Typical cost | The time itself | The time plus rush, overtime, scrap and missed orders |
| How you reduce it | Make it shorter, schedule it smarter | Prevent the cause, recover faster |
Breaks and time with no production planned are removed before OEE is calculated, so they do not count as a loss.
Stops inside planned production time reduce availability, whether they were planned or not. That includes changeovers and in-shift maintenance.
Maintenance done in a window outside planned production time, such as a weekend shutdown, does not reduce OEE. Our OEE calculation guide walks through the formula with worked examples.
A changeover with a 20-minute standard that takes 35 minutes contains 15 minutes of unplanned downtime.
The same applies to a maintenance task that runs past its window, as our guide to preventive maintenance overruns explains.
Record the overrun separately, or it hides inside a stop everyone thinks is under control.
| Source | Typical causes and first countermeasure |
|---|---|
| Equipment | Causes: Wear, lubrication problems, misalignment, electrical and sensor faults First countermeasure: Preventive maintenance on the repeat failures |
| Process | Causes: Jams, misfeeds, product out of spec, wrong settings First countermeasure: Fix the station that stops most often |
| People | Causes: No operator or technician available, unclear responsibilities, skipped steps First countermeasure: Clear roles, standard work and training |
| Supply | Causes: Missing material, packaging or tools First countermeasure: Kitting and a check before the shift starts |
| Quality | Causes: Holds while a defect is investigated First countermeasure: Faster decisions and process checks at the source |
| Utilities and IT | Causes: Power dips, compressed air, network or control system faults First countermeasure: Record them separately and review with facilities and IT |
In many plants, the total is driven by a few repeat failures plus many shorter interruptions. Both only become visible when every stop is recorded with a reason.
Very short stops, often under two minutes, are usually tracked as micro stops and count as a performance loss in OEE.
| Metric | Formula | What it tells you |
|---|---|---|
| Unplanned downtime rate | Unplanned downtime ÷ planned production time × 100 | How much planned time is lost to surprises |
| Unplanned share | Unplanned downtime ÷ total downtime × 100 | How much of your downtime was not scheduled |
| Number of stops | Count of unplanned stop events | Whether you have a frequency problem |
| MTBF | Run time ÷ number of failures | How long equipment runs between failures |
| MTTR | Total repair time ÷ number of repairs | Whether you have a recovery problem |
For more on the last two, see our guide to MTBF and MTTR.
A packaging line runs two 450-minute shifts, after breaks, on 20 days a month, so planned production time is 18,000 minutes. The numbers are an illustration, so replace them with your own.
It has 40 changeovers a month at a 20-minute standard, which is 800 minutes of planned downtime. The unplanned stops longer than two minutes look like this:
| Cause | Stops | Minutes | Share (rounded) |
|---|---|---|---|
| Breakdowns | 6 | 390 | 39.4% |
| Jams over 2 minutes | 40 | 200 | 20.2% |
| Material shortages | 8 | 160 | 16.2% |
| Changeover overruns | 10 | 150 | 15.2% |
| Quality holds | 3 | 90 | 9.1% |
| Total | 67 | 990 | 100% |
Breakdowns and jams together account for 590 of the 990 minutes, which is 59.6%. That is where to start.
The line packs 80 units a minute, with a contribution margin of €0.40 per unit, so each lost minute is worth €32 of margin.
If the output is lost for good, the month costs 990 × €32 = €31,680 in margin, before repair labor and parts.
If the plant makes the volume up with overtime, it needs at least 16.5 hours (990 minutes) of extra running time.
With a crew of five paid €40 an hour each, that is 16.5 × 5 × €40 = €3,300, plus repair labor, parts and any rush freight.
Use the version that matches reality. A cost figure that assumes every minute is lost margin quickly stops being believed.
For a fuller cost model, see how to calculate the true cost of unplanned downtime.
Suppose preventive maintenance on the failing components halves breakdown time to 195 minutes, and guide and sensor fixes cut jam time by 40% to 120 minutes.
Unplanned downtime falls by 195 + 80 = 275 minutes, to 715 minutes. The unplanned downtime rate drops to 4.0%.
Availability rises to 91.6%, assuming the extra maintenance is done outside planned production time.
The 275 recovered minutes are worth 22,000 units, or €8,800 a month in margin, if the plant can sell them.
If the plant was making the volume up with overtime, the saving is about 4.6 crew hours of overtime a month, roughly €920.
Siemens' report The True Cost of Downtime 2024 estimates that the world's 500 biggest companies lose almost $1.4 trillion a year to unplanned downtime, equivalent to 11% of their revenues.
Its survey of 181 maintenance, engineering and IT professionals at large industrial organizations in automotive, FMCG, heavy industry and oil and gas found that an average large plant loses 27 hours a month to unplanned downtime.
Plants averaged 25 downtime incidents a month, based on responses collected from April 2019 to March 2023.
Averages like these are useful for context. Your own stop log is what tells you where to act.
| Strategy | When, effect and what it needs |
|---|---|
| Reactive | When work happens: After a failure Effect on unplanned downtime: Every failure on a running line becomes unplanned downtime What it needs: Fast response and spare parts |
| Preventive | When work happens: On a calendar or usage interval Effect on unplanned downtime: Prevents many failures that follow a predictable wear pattern What it needs: A maintenance plan and discipline |
| Condition-based | When work happens: When a measured condition crosses a limit Effect on unplanned downtime: Catches wear that does not follow a fixed interval What it needs: Sensors or inspections, and agreed limits |
| Predictive | When work happens: When a model forecasts a failure Effect on unplanned downtime: Can act earlier on critical assets What it needs: Good failure history, data and specialist skills |
Many plants use a mix. Start with preventive maintenance on your repeat failures, then add condition-based maintenance where wear is irregular and the asset is critical.
Machine data captures the stops operators do not write down, with exact start and end times.
Use a short reason list that operators can pick in seconds. See our guide to downtime reason codes.
A Pareto chart shows the few causes worth fixing first, as the example did.
If the same component fails again and again, service or replace it before it fails, based on run hours or cycles.
Resetting a trip gets the line running. Finding out why it tripped stops it from happening next week.
The 5 whys is a simple place to start.
A short repair becomes a long stop when the part is not on the shelf. Our guide to spare parts inventory management explains how to decide what to hold.
Measure every changeover against its standard and shorten the long ones with SMED.
Confirm material, packaging, tools and staffing before the line needs them, so the line never waits.
For 15 methods in more depth and a second worked example, read how to reduce machine downtime.
Fabrico is an OEE platform with a full CMMS built in.
It collects machine data through PLC connections, IoT sensors and AI cameras, records stops as they happen and detects micro stops.
Downtime, MTTR and MTBF analytics show which machines and causes lose the most time, and you can export the data to Excel.
Because maintenance lives in the same platform, your team can open work orders, schedule recurring preventive maintenance and track spare parts without switching tools.
Push, in-app and email notifications with configurable rules keep the right people informed.
Want to see where your unplanned downtime really comes from? Book a demo.
Yes. Every unplanned stop inside planned production time lowers availability, the first OEE factor.
Very short stops are usually the exception, because they are counted as a performance loss instead.
Planned downtime is scheduled and prepared in advance, such as a changeover or a maintenance window. Unplanned downtime happens without warning.
Both reduce output, but unplanned downtime usually costs more for the same length of stop.
Divide unplanned downtime by planned production time and multiply by 100.
In the example above, 990 minutes out of 18,000 gives 5.5%.
If the output is lost, multiply the lost minutes by your output rate and contribution margin, then add repair labor and parts.
If you make the output up later, count the overtime, rush costs and repair costs instead.
A changeover is planned downtime up to its standard time. Any time beyond the standard is best recorded as unplanned downtime.
Usually, fixing the repeat failures and the station that stops most often.
Those problems keep coming back, so each fix pays off every week, and a stop log shows exactly where they are.
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