AI
AI-Driven Predictive Maintenance for a Global Manufacturer
Global manufacturing conglomerate
Machine learning models that forecast equipment failures, cutting unplanned downtime and maintenance costs.
Challenge
Frequent unplanned downtime and inefficient data usage were hurting productivity, with 80,000+ retro invoices a month across 1,000+ vendors on MSETU in varied formats. Maintenance was reactive.
What we did
- Deployed ML models to predict failures from historical and external data.
- Applied data analytics to surface hidden patterns and performance trends.
- Built interactive dashboards for real-time visibility and decision-making.
- Automated data retrieval from multiple sources to reduce manual effort.
- Implemented anomaly detection and timestamp reconciliation for accurate insights.
Results delivered
- ✓High accuracy in predicting equipment failures.
- ✓Significant reduction in unplanned downtime.
- ✓Lower maintenance costs and optimized resource allocation.
- ✓Improved operational efficiency and equipment performance.
- ✓Scalable solution supporting future digital expansion.