Analysis reportJuly 1, 2026
Manufacturing KPI Dashboard
- Source
- sample-data.csv · 8 rows
OEE
74%
+1.9ppFirst-pass yield
96.2%
+0.4ppUnplanned downtime
18.4h
-3.1hOn-time delivery
93%
+1.2ppOEE by week
Sample data — trailing 8 weeks
Manufacturing KPI dashboard
Manufacturing dashboards succeed when they stay on the OEE trinity — availability, performance, quality — and fail when they drown the plant floor in forty metrics nobody can move. Five numbers, trended, beat a wall of gauges.
Live render with sample data — upload your own export and this structure regenerates from your numbers, with the computation attached to every figure.
The manufacturing KPIs that matter, defined
- Overall equipment effectiveness (OEE)
- Availability × performance × quality. World-class is ~85%; most plants run 60–75%, and the decomposition tells you which of the three to attack.
- Availability × Performance × Quality
- First-pass yield
- Units passing inspection without rework divided by units started. Rework hides real yield problems — first-pass is the honest number.
- Good units first time ÷ Units started × 100
- Unplanned downtime
- Hours lost to unscheduled stops. Trend it per line and per cause code so maintenance priorities come from data.
- Scrap rate
- Material scrapped divided by material consumed — the direct cost-of-quality metric.
- Scrap ÷ Total material × 100
- On-time delivery (OTD)
- Orders shipped by promise date divided by orders shipped. The customer-facing summary of everything upstream.
Frequently Asked Questions
Everything you need to know about using AnalyzeData.
OEE with its three components, first-pass yield, unplanned downtime by cause, scrap rate, and on-time delivery. That set covers equipment, quality, and customer outcomes without gauge overload.
Export production runs, downtime logs, and quality checks as CSV, upload, and ask for the weekly plant review. Calculations like OEE decomposition run as visible code on the export.
Because OEE is availability times performance times quality, and one blended figure like 74% hides which of the three is dragging. A plant losing points to downtime needs a completely different fix than one losing them to slow cycles or scrap. Always read OEE through its decomposition. For context, world-class runs around 85% and most plants sit at 60-75%, but the components, not the headline, tell you where to act.
Because rework hides the real problem. Final yield counts units that passed after being reworked, so a line can look healthy while quietly burning labour fixing defects. First-pass yield, good units the first time divided by units started, is the honest number, and the gap between it and final yield is exactly the cost of quality your process is absorbing. Trend it to see whether that hidden cost is growing.
Build your manufacturing KPI dashboard
Upload the export you already have — the dashboard computes itself, verifiably.
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