Case Study
Preventing Downtime with AI-Driven Predictive Maintenance
IoT-integrated platform that forecasts failures, monitors machine health in real time, and orchestrates proactive maintenance.
Project Overview
A manufacturing firm suffered frequent breakdowns and high maintenance costs. Schedules were reactive and visibility into machine health was limited. Keylent built a Predictive Maintenance System that ingests IoT sensor data, forecasts failures with time-series and anomaly models, and triggers proactive actions,integrated with MES/ERP and deployable at edge or cloud.
Key Challenges
Unplanned Downtime
Inefficient Maintenance Schedules
Limited Machine Health Visibility
MES/ERP Integration Needs
Our Solution
- Failure Prediction Models
- Real-Time Monitoring Dashboards
- IoT & MES Integration
- Edge + Cloud Deployment
Key Technologies
Impact
65%
Reduction in equipment downtime
40%
Decrease in maintenance costs
90%
Increase in machine health visibility
Client Testimonial
“The AI models are accurate and actionable. Real-time dashboards give us full control over machine health and the savings are massive.”
— Director of Operations, Global Manufacturing Firm