Blog · Board and management reporting · Manufacturing
Production dashboards compare completed output, downtime, and scrap by plant and shift. Work through a production export, reconcile the totals, and identify the losses each team should investigate.
Production dashboards compare good output, downtime, and scrap by plant and shift so operations teams can see where production fell short and which records explain the gap. A useful dashboard for production starts with a closed period, a consistent unit, and totals that reconcile to the production export. The practical result is a list of losses to investigate and owners who can act on them.
The first question is whether the plant produced the accepted units it planned to produce. The next questions are how much scheduled time was lost and how much completed production became scrap. Read those measures together: a high total count can hide poor quality, while a low scrap rate can coexist with a large delivery shortfall.
NIST's research on manufacturing performance indicators describes relationships among measures of throughput, availability, quality, and maintenance. That supports reviewing connected measures rather than treating an isolated percentage as a complete account of performance.
Use a small, stable set of definitions:
Good units = Total units produced − Scrap units
Target attainment = Good units / Target good units
Scrap rate = Scrap units / Total units produced
Downtime rate = Recorded downtime minutes / Planned production minutes
The good-units identity here assumes every completed unit has a final disposition of good or scrap. A plant with rework or inspection holds needs those additional statuses in its reconciliation. A broader operational dashboard can combine production with other functions; this view stays with the production period and its records.
Use one row per plant, line, product, and shift, or retain individual production runs and summarize them to that level. Keep the run identifier, production date, unit of measure, target version, and export cutoff. Get targets from the schedule approved before the period, rather than replacing them with actual production afterward.
Use a separate stop-event register if each production run has several stop records. Total the nonoverlapping stops for each run before attaching that result to the production row. Otherwise, repeating the production count against each stop reason multiplies output.
Here is an illustrative US manufacturer making the same component at two plants on October 21, 2026. All counts are individual components. Planned production minutes already exclude periods when production was not scheduled; downtime includes recorded stops inside that planned window.
| Plant | Shift | Planned minutes | Downtime minutes | Target good units | Total units | Scrap units |
|---|---|---|---|---|---|---|
| Ohio | Day | 450 | 45 | 900 | 840 | 30 |
| Ohio | Night | 450 | 75 | 900 | 780 | 45 |
| Indiana | Day | 450 | 30 | 900 | 900 | 18 |
| Indiana | Night | 450 | 90 | 900 | 750 | 60 |
| Total | 1800 | 240 | 3600 | 3270 | 153 |
Do not add unlike quantities into this count. A plant making components and another making bulk material need separate units or an explicitly defined common measure. Production share answers a different question about each group's portion of a stated total.
Subtract scrap from total units, then divide by the relevant denominator. Rates below are rounded to one decimal place after calculation; counts and minutes remain exact.
| Plant | Shift | Good units: total − scrap | Target attainment | Scrap rate | Downtime rate |
|---|---|---|---|---|---|
| Ohio | Day | 840 − 30 = 810 | 810 / 900 = 90.0% | 30 / 840 = 3.6% | 45 / 450 = 10.0% |
| Ohio | Night | 780 − 45 = 735 | 735 / 900 = 81.7% | 45 / 780 = 5.8% | 75 / 450 = 16.7% |
| Indiana | Day | 900 − 18 = 882 | 882 / 900 = 98.0% | 18 / 900 = 2.0% | 30 / 450 = 6.7% |
| Indiana | Night | 750 − 60 = 690 | 690 / 900 = 76.7% | 60 / 750 = 8.0% | 90 / 450 = 20.0% |
| Total | 3270 − 153 = 3117 | 3117 / 3600 = 86.6% | 153 / 3270 = 4.7% | 240 / 1800 = 13.3% |
The total ratios divide summed numerators by summed denominators. Never average the displayed row percentages. Even when equal denominators make one average happen to work, that shortcut fails as soon as shift duration or planned volume changes.
For a repeatable spreadsheet layout with the input columns and calculation cells separated, use the production dashboard template.
Two identities should close exactly:
| Check | Calculation | Result |
|---|---|---|
| Output disposition | 3117 good + 153 scrap − 3270 total | 0 units |
| Time allocation | 1560 run + 240 downtime − 1800 planned | 0 minutes |
The run minutes are 1800 − 240 = 1560. Verify good and scrap counts against the production and quality registers, and planned minutes against the shift schedule. The time identity alone cannot detect duplicated stop records if run time was calculated by subtraction; review event overlaps separately.
Keep this downtime definition visible. The OEE calculation guidance from Vorne includes both planned stops, such as changeovers, and unplanned stops within planned production time. An unplanned-downtime-only measure uses a narrower numerator and needs that label. See the OEE dashboard method when the question requires availability, speed, and first-pass quality together.
The plant totals are close enough to obscure the shift pattern. Ohio produced 1545 good units and Indiana produced 1572, but the shift comparison is more informative:
| Shift | Target good units | Total units | Scrap units | Good units | Downtime minutes | Target attainment |
|---|---|---|---|---|---|---|
| Day | 1800 | 1740 | 48 | 1692 | 75 | 94.0% |
| Night | 1800 | 1530 | 105 | 1425 | 165 | 79.2% |
The night supervisor should review stop reasons and staffing records with maintenance. Quality should review the scrap dispositions and product lots; the quality assurance dashboard develops that separate investigation. These results identify where to look, but they do not prove that a particular employee, machine, or material caused the losses.
Record the action, owner, and next review date beside the finding. Planning owns a target correction if the schedule was wrong. Maintenance owns investigation of equipment stops. Quality owns defect classification and containment decisions. Operations owns the combined follow-up.
Bring a sample of your own production export, matching targets, and downtime records: Covirage maps the columns, and its tools compute and check the output, scrap, and time measures. 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 your file.
See Covirage for industrial manufacturers for the manufacturing context.
Include good units against the approved production target, total units, scrap units and rate, planned production minutes, and recorded downtime. Show the reporting period and product scope beside the results. Break the same measures down by plant and shift so readers can identify where the total changed.
Update them after the production and quality records for the reporting period are complete enough to compare. A shift review can use provisional counts if they are clearly labeled. A weekly report should identify late corrections and use the same cutoff across all included plants.
Total output includes units produced regardless of their disposition. Good output includes only units accepted under the report's stated rule. Keep scrap, rework, and units awaiting inspection separate when those statuses exist; subtracting scrap alone does not establish good output if other unresolved units remain.
Operations should own the reporting definition and review. Shift supervisors verify counts and stop records, quality verifies dispositions, and production planning maintains the target. The report needs one accountable owner to resolve differences before a comparison becomes the basis for a scheduling or improvement decision.