AI for Manufacturing

The Problem

Unplanned equipment failures cost manufacturers an average of $50K-250K per incident in lost production, emergency repairs, and downstream delays. Reactive maintenance is expensive, and calendar-based preventive maintenance often replaces parts too early or too late. Meanwhile, valuable sensor data streams go unanalyzed.

Our Approach

We connect to your existing IoT sensor infrastructure and build equipment-specific anomaly detection models that learn normal operating patterns for each machine class. The system detects degradation signatures weeks before failure, giving maintenance teams time to plan repairs during scheduled downtime. We work with your maintenance engineers to validate predictions against their experience.

Technology

Results You Can Expect

45% reduction in unplanned downtime, 2-3 weeks advance failure warning, $1M+ annual savings from prevented failures.

Who This Is For

• VP of Manufacturing
• Plant Manager
• Maintenance Director