Blog · Board and management reporting · Manufacturing
A downtime dashboard compares stopped minutes, event frequency and potential production loss by machine and shift. A worked event log shows the calculations, cost assumptions and checks that prevent double counting.
A downtime dashboard compares stopped production time, event frequency and potential output loss by machine and shift. Start with the historical event log and the production schedule, then separate the operational loss from the financial assumptions used to value it.
The useful result is a ranked set of operating questions: which causes consumed time, where they repeated, and whether the lost capacity affected orders. Stopped minutes alone do not answer all of them.
An illustrative US component manufacturer reviews a day shift and a night shift on September 15, 2026. Machines A and B each have 480 planned production minutes per shift. Each machine therefore has 960 planned minutes, and the combined denominator is 480 × 2 × 2 = 1,920 machine-minutes.
The chosen window includes changeovers that occur during scheduled production. Breaks and other excluded periods have already been removed from the stated schedule. Keep this boundary visible beside the result; do not remove a stop from the numerator while leaving its time in the denominator.
Pacific Northwest National Laboratory's maintenance KPI guidance expresses availability as uptime over expected operating time, including planned downtime. It also distinguishes maintenance measures with different denominators. Your dashboard should state exactly which window its availability measure uses rather than relying on the label alone.
The production manager owns the schedule and reason categories. Maintenance confirms equipment-related causes. Finance owns any contribution assumptions. The shift supervisor checks that logged starts and finishes describe what actually happened.
Every event below occurs within its machine's scheduled production window. Times use the site's local clock. The rows do not overlap, and all events start and finish on the stated date. The expected rates are planning inputs for the product assigned to each machine: A makes 4 units per minute and B makes 3.
| Event | Machine | Shift | Stop | Restart | Cause | Duration (minutes) | Expected units/minute | Potential units |
|---|---|---|---|---|---|---|---|---|
| E01 | A | Day | 08:20 | 08:50 | Material jam | 30 | 4 | 120 |
| E02 | A | Day | 10:00 | 10:20 | Sensor fault | 20 | 4 | 80 |
| E03 | A | Night | 20:10 | 20:50 | Material jam | 40 | 4 | 160 |
| E04 | B | Day | 09:00 | 10:00 | Material shortage | 60 | 3 | 180 |
| E05 | B | Night | 19:00 | 19:30 | Planned changeover | 30 | 3 | 90 |
| E06 | B | Night | 22:00 | 22:20 | Tool adjustment | 20 | 3 | 60 |
| Total | 200 | 690 |
The duration is restart time minus stop time. Potential units equal duration multiplied by the expected rate for that event; E04 is 60 × 3 = 180 units. Summing the individual estimates gives 120 + 80 + 160 + 180 + 90 + 60 = 690 potential units.
This estimate describes capacity exposure during stops. It does not establish that customer orders were lost, that the expected rate was achievable throughout the shift, or that production was never recovered later. Keep actual accepted production beside the estimate when reviewing commercial consequences.
Running minutes = Planned production minutes - Stopped minutes
Availability = Running minutes / Planned production minutes
Average stop duration = Stopped minutes / Number of events
| Machine | Planned minutes | Events | Stopped minutes | Running minutes | Availability | Potential units |
|---|---|---|---|---|---|---|
| A | 960 | 3 | 90 | 870 | 90.6% | 360 |
| B | 960 | 3 | 110 | 850 | 88.5% | 330 |
| Total | 1,920 | 6 | 200 | 1,720 | 89.6% | 690 |
Percentages are rounded to one decimal place after calculation. Machine A's availability is 870 / 960 = 90.6%; the combined result is 1,720 / 1,920 = 89.6%. Average stop duration is 200 / 6 = 33.3 minutes, also rounded to one decimal place. This average includes a changeover and a material shortage, so it should not be labeled mean time to repair.
| Shift | Planned machine-minutes | Events | Stopped minutes | Potential units |
|---|---|---|---|---|
| Day | 960 | 3 | 110 | 380 |
| Night | 960 | 3 | 90 | 310 |
| Total | 1,920 | 6 | 200 | 690 |
The day shift loses more time and more potential units. Machine A loses fewer minutes than B, yet more potential units because its planned rate is higher. That is why the production rate belongs in the event detail rather than applying one plantwide rate to every stop.
Availability is also only part of equipment effectiveness. The NIST report on manufacturing maintenance measures describes an OEE calculation using availability, performance and quality. This example has no measured running-speed or quality factors, so its availability percentage is not an OEE result.
| Cause | Events | Stopped minutes | Share of stopped time |
|---|---|---|---|
| Material jam | 2 | 70 | 35.0% |
| Material shortage | 1 | 60 | 30.0% |
| Planned changeover | 1 | 30 | 15.0% |
| Sensor fault | 1 | 20 | 10.0% |
| Tool adjustment | 1 | 20 | 10.0% |
| Total | 6 | 200 | 100.0% |
Material jams lead on lost time: (30 + 40) / 200 = 35.0%. The material shortage is the longest individual event. These point to different review questions: repeated jams require a recurrence review, while the shortage requires an explanation of why scheduled material was unavailable.
Assume finance approves an illustrative contribution of $8 per additional unit sold for both products. Potential contribution exposure is 690 × 8 = $5,520. Contribution means sales less the incremental costs specified by finance; it is not the selling price. Use the manufacturing cost analysis to establish the cost boundary and keep actual repair expense in its own column.
Change only E03's duration from 40 to 20 minutes, leaving event count, product rates, schedules and contribution per unit unchanged. The event now restarts at 20:30.
| Measure | Original case | Shorter-stop case |
|---|---|---|
| E03 stopped minutes | 40 | 20 |
| E03 potential units | 160 | 80 |
| Combined stopped minutes | 200 | 180 |
| Combined running minutes | 1,720 | 1,740 |
| Combined availability | 89.6% | 90.6% |
| Combined potential units | 690 | 610 |
| Potential contribution exposure (USD) | 5,520 | 4,880 |
The change releases 20 × 4 = 80 units of potential capacity and reduces exposure by 80 × 8 = $640. It does not eliminate an event: frequency remains 6. A spending decision still needs evidence that the released capacity serves demand and that the proposed fix costs less than its justified benefit; see manufacturing operational ROI.
The schedule identity is 1,720 running + 200 stopped = 1,920 planned machine-minutes. Both the machine and shift tables must return 200 stopped minutes and 690 potential units. The cause table must return the same 6 events and 200 minutes. These are practical reconciliation checks, not optional display details.
Do not add machine-minutes together and call them elapsed plant downtime. These machines can stop simultaneously. If they are sequential steps on the same line, summing both output estimates can also count the same lost production twice; estimate the line's constrained output separately.
Upload the event log, production schedule and approved rate assumptions. Covirage maps the columns; its tools compute and check the figures, and the external AI model explains the results with every figure traced to its rows. Create a free Covirage account, which takes about a minute, then set up your business and bring a sample of your own data.
See Covirage for industrial manufacturers for the wider operating and financial review.
Downtime is stopped time within a defined operating window. Availability expresses running time as a share of the planned production time in that window. The same downtime duration can produce different availability results when machines have different schedules, so show both the minutes and denominator.
Include them when they occur inside the production window you have chosen, and label them separately from unplanned failures. Exclude time outside that window consistently. A change in the treatment of changeovers can move the reported availability even when the operating events are identical.
Estimate potential output using stopped minutes and a justified production rate, then apply the contribution per unit. Label the result as exposure. Confirm demand, bottleneck effects and later recovery before calling it lost profit, and record repair spending separately from the opportunity estimate.