The Challenge
No visibility into production metrics, unpredictable downtime.
Technical Implementation
IoT platform with predictive maintenance 48 hours ahead.
Project Timeline
Sensor Audit
3 weeksAssessed 500+ machines, identified data sources and integration points
IoT Pipeline
5 weeksMQTT broker cluster, real-time stream processing with Python
ML Models
4 weeksTrained predictive maintenance models on 2 years of historical data
OEE Dashboards
3 weeksReal-time dashboards for plant managers, supervisors, and operators
Full Deployment
3 weeksRolled out across 3 plants, integrated with existing MES and SCADA
Results in Detail
TechnoBuilt Industrial gained complete visibility into its manufacturing operations. The predictive maintenance models now provide 48-hour advance warning of equipment failures, reducing unplanned downtime by 65%. Overall Equipment Effectiveness (OEE) improved by 22%, and the system paid for itself within 4 months through avoided downtime and increased production throughput.
Operational Impact
- 65% less unplanned downtime.
- Real-time OEE tracking for leadership.
- Simple dashboard for all teams.
“For the first time, we have complete visibility into our production floor. The predictive maintenance alone has saved us millions in avoided downtime.”
Vikram Singh
Director of Manufacturing, TechnoBuilt Industrial
Technologies Used
“For the first time, we have complete visibility into our production floor. The predictive maintenance alone has saved us...”
Vikram Singh
Director of Manufacturing, TechnoBuilt Industrial
Ready to scale?
Have a similar challenge? Let's discuss how we can help your business.
Discuss your project