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Work · Manufacturing / Logistics
A real-time operations dashboard for the production floor
Replacing end-of-shift paper logs with live OEE, downtime, and throughput monitoring for a regional manufacturer's production floor.
blueprint21 May 2026
up to 50%
Downtime reduction after adopting real-time analytics (McKinsey)
up to 15%
Productivity gain from real-time performance tracking (McKinsey)
86%
Manufacturers who say smart-factory initiatives will drive competitiveness (Deloitte)
This is a solution blueprint — a reference architecture we can build for your business. The figures above are cited industry benchmarks for this class of system, not results claimed for a named client.
The pipeline we'd build
4 stages
Stage 01 · OEE score
OEE is defined once, so the floor and the office argue about the decision rather than the number.
The challenge
A regional manufacturer only discovered downtime and quality issues after shift-end paper logs were compiled the next morning, losing hours of actionable response time on every incident.
What we did
We deploy a streaming ingestion layer from MES and PLC sensor feeds into TimescaleDB, surfaced through a Grafana floor dashboard refreshing every 15-60 seconds with OEE, downtime events, and utilization by line.
The outcome
McKinsey's manufacturing-analytics research documents downtime reductions of up to 50% and productivity gains of 10 to 15% when floors move from periodic to real-time monitoring — consistent with the pattern this dashboard targets.
Stack
Python (FastAPI)TimescaleDBGrafanaMQTT
A paper log compiled at the end of a shift tells you what went wrong yesterday, not what's going wrong right now. McKinsey's manufacturing-analytics research finds real-time monitoring can cut downtime by up to 50% and lift productivity by 10 to 15% simply by shortening the gap between a fault occurring and someone being able to act on it.
From shift-end log to live floor view
Sensor and MES data streams into TimescaleDB (a time-series-optimized layer over Postgres) via MQTT, and a Grafana dashboard on the floor refreshes every 15-60 seconds with live OEE, active downtime events, and per-line utilization — visible to the people who can actually act on it, not just to a report someone reads the next day.
Real-time floor monitoring pipeline
From shop-floor sensors to a live dashboard — a blueprint of standard components
Shop floorIngestionStorageDashboard
Tap any component above for its role and the real tech.
A blueprint of standard components — adapted to your existing MES/PLC systems, not a fixed template.
- PLC / sensors (Client, Machine-level telemetry): Existing shop-floor sensors and PLCs — nothing new to install on the machines themselves.
- MQTT broker (API, Lightweight IoT messaging): Queues and delivers sensor readings even through brief network interruptions.
- FastAPI ingest (Service, Python): Validates and writes incoming readings into the time-series store.
- TimescaleDB (Data, Time-series extension over Postgres): Optimized for high-frequency sensor writes and time-range queries.
- Grafana dashboard (Service, 15-60s refresh): Live OEE, downtime events, and utilization, visible on the floor itself.
The same 'don't wait for the end-of-period report' philosophy applies to office-side reporting too — see our executive KPI dashboard blueprint for the equivalent pattern applied to finance and leadership reporting rather than the production floor.
At a glance
Client
Solution blueprint
Sector
Manufacturing / Logistics
Service
Data & Analytics
Kind
blueprint
Headline result
up to 50% · Downtime reduction after adopting real-time analytics (McKinsey)
Handover
Documented, tested code in your repository
Questions we were asked
Is up to 50% downtime reduction realistic, or best-case?
McKinsey's manufacturing-analytics research cites this as an achievable range, not a guarantee — it depends heavily on how much of today's downtime is actually detectable from sensor/MES data versus caused by factors outside the monitoring scope (e.g. supply chain delays).
Do we need to replace our existing MES system?
No — the ingestion layer reads from your existing MES/PLC feeds; it doesn't require replacing the underlying manufacturing execution system.
What happens if the network to the floor goes down?
MQTT is designed for exactly this — it queues messages and delivers them once connectivity resumes, so a brief network interruption doesn't lose data, just delays the dashboard update.
Same problem, different business?
We'll send the architecture and a realistic timeline for your version of this — no obligation.