Novelis, a global aluminum producer, moved from a traditional preventive maintenance strategy—marked by scheduled downtime and unexpected failures—to AI-driven predictive maintenance using SymphonyAI Predictive Asset Intelligence, combining rule-based and machine-learning alerts to build trust and accelerate adoption. This shift improved real-time asset health monitoring, reduced unplanned downtime across facilities, and fostered collaboration among engineers, data scientists, and reliability teams. By embedding predictive insights into workflows, Novelis enhanced responsiveness to customer demand, drove proactive problem-solving, and advanced its vision of a “plant of the future” with a culture of continuous improvement and innovation.

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