Manufacturing: AI Work Order Prioritization
Deployed ML models to predict and prioritize work orders based on failure impact and urgency.
Project Details
The Challenge
A global automotive manufacturer was experiencing frequent unplanned downtime due to equipment failures. Manual work order prioritization led to critical assets failing while resources were allocated to less important maintenance tasks, resulting in production delays and quality issues.
Our Solution
We developed an AI-powered work order prioritization system that: • Analyzed historical failure data and maintenance patterns • Integrated real-time sensor data from production equipment • Implemented machine learning models to predict failure probability • Automated work order priority scoring based on business impact • Created dashboard interfaces for maintenance planners
Implementation Timeline
Results Achieved
Technologies Used
"The AI prioritization system has transformed how we approach maintenance. We now prevent failures before they happen instead of just reacting to them."
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