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$5.3M saved in 30 days with AI Predictive Maintenance
We partnered with a global leader in aluminium manufacturing to help them with real-time monitoring, proactive defect detection, & advanced analytics by building an AI-powered predictive maintenance solution. In the first month of deployment, our solution prevented a critical equipment failure with its smart alert features, avoiding 168 hours of downtime and delivering $5.3M in savings.
The Challenge
- Financial Impact: Significant financial losses annually due to operational inefficiencies and unplanned disruptions.
- Production Disruption: Unplanned downtimes impacting production schedules
- Operational Costs: Production delays from equipment failures and supply chain disruptions result in increased overhead costs.
- Customer Relations: Customer dissatisfaction due to missed deadlines and quality issues.
Our Solution
- Data Processing & Collection: Sensor data collection and processing enable actionable insights for ops decision-making.
- Real-Time Monitoring System: Continuous monitoring using AI provides quick identification of anomalies and equipment issues.
- Predictive Framework: Advanced forecasting models predict potential equipment failures, minimizing unplanned downtime.
- Maintenance Management: Customizable alert creation & resolution with multiple action capabilities for proactive maintenance.
Business Benefits
- Cost Savings: Delivered $5.3M savings by preventing equipment failure, with potential savings of $10M+ annually preventing similar incidents.
- Predictive Maintenance: Early equipment defect detection minimized downtime and loss of production.
- Smart Alert Management: Advanced configuration eliminates false positives, ensuring only actionable notifications.
- User Empowerment: Enabled operators to independently configure and customize alerts using their domain expertise.
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