From a Manual Production Status Board to a Dashboard That Updates Itself
An illustration of an internal web app for a factory/manufacturer that needs real-time visibility into production line status and defect detection.
This is an illustrative concept, not a real client project — the data and results shown are examples to demonstrate what we can build.
Production lines keep running. But status is logged manually on a whiteboard.
When production status and defects are logged manually per shift, management only learns of a production problem after the daily report is done, not when it happens.
| Production Line | Daily Target | Status |
|---|---|---|
| Line A | 1,200 units | On Track |
| Line B | 950 units | Below Target |
| Line C | 1,400 units | On Track |
| Line D | 800 units | High Defects |
It's not a lack of capacity. It's that status isn't visible in real time.
Line status logged manually per shift
Supervisors log output and defects on a whiteboard/paper, then recompile it manually.
Defects only discovered in the daily report
Production quality issues are often only noticed after a shift ends, not when they occur.
Management has no real-time picture
Production decisions are made based on data that's already hours old.
One flow from production running to status monitored in real time.
Output and defects are logged digitally, so management can make decisions faster.
Production Running
The production line runs, output logged automatically per unit.
Log Defect
Operators log defects directly from the app, not paper.
Real-time Monitoring
Each line's status is visible in real time from the dashboard.
Anomaly Alert
Automatic notification when the defect rate or output falls outside normal range.
Automatic Report
A daily production summary is available automatically per line.
Example: a factory with 6 production lines.
An illustrative scenario based on common patterns at medium-sized factories/manufacturers. The figures below are examples to illustrate the system, not a claim of client results.
Real-time multi-line production dashboard
The factory has 6 production lines each with its own daily target. Status and defects are logged manually on a whiteboard, delaying management's decisions.
- Which line is below target today?
- Which line has a high defect rate?
- Is there an anomaly that needs attention right now?
Illustrated automation architecture
EXCEPTION → a line's defect rate exceeds the normal threshold → automatic notification sent to supervisor & management
- 6
- Example Production Lines
- Real-time
- Output & Defect Status
- 1
- Automatic Alert
monitored in one dashboard
instead of a daily report
for production anomalies
The key change is when a production problem is discovered.
Before / manual whiteboard
- Line status logged manually per shift
- Defects only discovered in the daily report
- Management has no real-time picture
- Production decisions are often delayed
- Supervisors recompile data every shift
After / real-time production dashboard
- Output and defects logged digitally in real time
- Anomalies detected as they happen
- Management can decide faster
- Supervisors don't need manual recompiling
- Production reports available automatically
Not just an output log.
This dashboard can be developed gradually to fit the factory's needs.
Real-time output tracking
Each line's production status monitored automatically, visible from one dashboard.
Defect logging & detection
Defects logged digitally, anomalies detected automatically as they occur.
Automatic production reports
Daily/weekly summaries available automatically per production line.
From a whiteboard to a production dashboard, step by step.
- 01DISCOVERY
Map production & logging flow
Identify targets and the current way output and defects are logged.
- 02FOUNDATION
Build the production data structure
One standard data structure for output and defects per line.
- 03DASHBOARD
Build the real-time dashboard
A display of all production lines' status on one screen.
- 04DETECTION
Add anomaly detection
Automatic alert when output/defects fall outside normal range.
- 05OPTIONAL
Add further layers
If needed, IoT machine integration or predictive maintenance can be added.