Unplanned downtime cost calculator
What does unplanned downtime cost you each year, and how much of it could early warning prevent? Enter values from your own maintenance records and see the annual cost, the potential savings and the payback period.
- Annual cost of unplanned downtime
- €96,000
- Unplanned downtime per year
- 48 hours / year
- Cost per failure
- €16,000
- Estimated annual savings
- €16,800
- Production time regained
- 12 hours / year
- Payback period
- No investment entered
Savings by avoidable share
| Avoidable share | Annual savings |
|---|---|
| 10% | €6,720 |
| 20% | €13,440 |
| 30% | €20,160 |
| 40% | €26,880 |
Savings = stops × avoidable share × (duration × hourly loss + repair) × (1 − planned intervention cost)
This is a preliminary estimate, not a commitment to results. Actual savings depend on equipment, failure types, data quality and maintenance organisation; we recommend assessing it with your own records.
Would you like to firm up this estimate with your own maintenance records? Let's look at which failures could really have been detected early, using your data.
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How to use it
A
From your maintenance records, enter the number of unplanned stops per year and the average duration for one line or machine.
B
Add the hourly production loss and the repair cost per failure; choose the currency.
C
Change the avoidable share assumption and see how the savings change in the sensitivity table.
02
How is it calculated?
The cost of a failure has two parts: production lost during the stop (duration × hourly loss) and the repair itself. The annual cost is that times the number of stops per year.
Predictive maintenance does not eliminate failures; it detects some of them early and turns them into planned interventions. Planned work has a cost too, but it is usually shorter and needs fewer parts. The calculation therefore takes the cost of avoidable failures and subtracts the share of the planned intervention.
03
Which values should I enter?
The most reliable source is the last one or two years of maintenance work orders: how many unplanned stops each machine had, how long each lasted, which parts were replaced. For the hourly loss, think beyond the sales price: lost contribution margin, overtime and delay penalties.
Entering values for one critical machine gives a more meaningful result than averaging over the whole plant; predictive maintenance usually starts with the most critical equipment.
04
Why is the avoidable share an assumption?
Whether a failure can be detected early depends on the failure type (slowly developing faults such as bearings, gears or imbalance versus sudden breaks), sensor coverage and data quality. Rather than giving one fixed rate, the sensitivity table shows the result at different rates.
The way to see the real rate is to put past failures next to the sensor data and check which ones left a trace beforehand.
FAQ
- Are the values I enter sent anywhere?
- No. The calculation runs entirely in code inside your browser; the values are neither transmitted to a server nor stored.
- Where do the default values come from?
- The defaults are examples chosen only to show how the tool works; they are not an industry average or a measured result. Enter your own values for a meaningful result.
- Is the result a commitment?
- No, it is a preliminary estimate. Actual savings depend on equipment, failure types, data quality and maintenance organisation. Get in touch to firm it up with your own records.
- Which equipment is it for?
- Any equipment whose failure stops production: pumps, compressors, fans, conveyors, gearboxes, wind turbines, packaging lines. We recommend entering values for a single machine or line.
Catch the failure before it becomes downtime
We turn existing SCADA and sensor data into a health score per machine and early warnings before failure. Let's talk about your equipment and data in a free discovery call.