Bringing Real-Time Intelligence to the Manufacturing Shop Floor
An Industrial IoT platform that connects die-casting machines to the cloud for live monitoring, analytics, and production optimization.
What They Were Struggling With
Ahresty India operates dozens of die-casting machines across their manufacturing facility, running 24/7 in three shifts. Each machine generates critical data—shot counts, cycle times, metal consumption, operational status—but this data was siloed, delayed, and nearly impossible to act on.
Plant managers relied on end-of-shift paper reports to understand production. By the time issues surfaced, hours of production time had been lost. There was no way to compare machine performance, track hourly trends, or identify bottlenecks in real-time.
The technical challenge: connect industrial machinery to modern cloud infrastructure while ensuring reliability, handling network disruptions, and processing thousands of data points per hour.
How We Solved It
We built a complete Manufacturing Intelligence System that connects the shop floor to the cloud in real-time.
IoT Layer: Deployed sensors on each die-casting machine to capture cycle data, shot counts, and operational status. A local edge gateway aggregates and pushes data to the cloud via secure REST APIs.
Cloud Backend: Express.js API with MongoDB handles data ingestion, validation, and aggregation. Cron jobs run scheduled processing for MIS reports, shift summaries, and trend analysis.
Real-Time Dashboard: A Next.js 15 dashboard gives plant managers instant visibility into every machine—live status, hourly targets vs actuals, metal consumption trends, and exportable reports.
Reliability First: The system handles network disruptions gracefully with local buffering, retry mechanisms, and data integrity checks. 99.9% uptime since deployment.
What We Delivered
Live Dashboard
Real-time monitoring of all die-casting machines—status, shot counts, cycle times, and efficiency metrics at a glance.
Hourly Analysis
Track production targets vs actuals hour-by-hour. Identify underperforming shifts and machines instantly.
Metal Tracking
Precise aluminum consumption tracking per machine, per shift. Reduce wastage with per-machine tracking.
MIS Reports
Automated daily/weekly/monthly reports. Export to Excel with one click for management review.
Platform Showcase
Real-time shop floor overview with machine status
Shift-wise hourly production breakdown
Management reports with export functionality
Visual trends for production and efficiency
The Transformation
Before
- Paper-based end-of-shift reports
- 8+ hour delay in production visibility
- Manual metal consumption tracking
- No way to compare machine performance
- Issues discovered after production loss
After
- Real-time cloud dashboard for all machines
- Instant visibility into production metrics
- Automated per-machine metal tracking
- Side-by-side machine performance comparison
- Proactive alerts for underperforming machines
Development Journey
Discovery & Architecture
Site visit to understand shop floor operations, IoT sensor specifications, and data requirements.
Backend & Database
Express.js API development, MongoDB schema design with optimized indexes, and IoT data ingestion pipeline.
Frontend Dashboard
Next.js 15 dashboard with real-time updates, hourly analysis tables, and shift graphs.
IoT Integration
Edge gateway setup, sensor data validation, retry mechanisms, and reliability testing.
Deployment & Training
Production deployment, performance optimization, user training, and handover documentation.
Built With Modern Tech Stack
“For the first time, we can see what's happening on the shop floor in real-time. The hourly analysis has helped us identify and fix production bottlenecks we didn't even know existed.”
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