All Case Studies
ManufacturingAI
Predictive Maintenance for Manufacturing
Deployed ML-based predictive maintenance reducing unplanned downtime by 62% and saving $8.7M annually across 12 production lines.
62% reduction in unplanned downtime
$8.7M annual savings
94% prediction accuracy
12 production lines covered
scikit-learnTensorFlowApache KafkaAWS SageMakerGrafana
Challenge
A global manufacturer experienced $14M in annual losses from unplanned equipment failures across 12 production lines, with maintenance teams operating reactively.
Solution
We built a real-time sensor data pipeline with Apache Kafka, trained gradient-boosted and LSTM models for remaining useful life prediction, and deployed via AWS SageMaker with Grafana dashboards.
Results
Unplanned downtime dropped 62%, saving $8.7M annually. Maintenance teams now operate proactively with 94% prediction accuracy on critical equipment.