Background
Novelis is a global leader in the manufacturing sector, recognized as the world’s largest provider of flat-rolled aluminum and a leader in aluminum recycling. Employing approximately 13,000 people and operating in nine countries with 32 plants worldwide, Novelis specializes in four major segments: food and beverage, automotive, aerospace, and specialty products.
Strategic Objectives and Business Challenges
Novelis faced significant challenges in its efforts to move from preventive maintenance practices to predictive maintenance. Growing through acquisitions, Novelis facilities use many different systems, including a variety of ERP systems and historians. Additionally, its facilities have generations of equipment ranging from state-of-the-art to legacy equipment from the 1960s. Previously, Novelis relied on a preventive maintenance approach that involved scheduled equipment downtime, limiting production uptime and creating considerable pressure to meet increasing customer demands. Unexpected failures resulting from a preventive maintenance strategy caused production delays and elevated costs. Novelis leadership was determined to better anticipate potential failures, increase uptime, and monitor asset health in real-time with predictive maintenance.
Solution
To gain AI insights for predictive maintenance, Novelis chose SymphonyAI Predictive Asset Intelligence for its comprehensive approach, which combines rule-based and AI machine learning (ML) alerts. The combination of monitoring techniques offered reassurance that alerts were accurate and built trust and confidence in the recommendations as they adopted proactive maintenance. By starting with rule-based alerts and gradually incorporating AI/ML alerts, Novelis adopted insights incrementally, reassuring stakeholders of the system’s reliability and fostering adoption across its diverse operations.
Impact
The implementation of SymphonyAI’s AI-based predictive asset intelligence products has yielded tangible benefits for Novelis, most notably in reducing unplanned downtime across multiple facilities. By embedding predictive insights into its workflows, Novelis has democratized insights across its operations and enhanced collaboration between process engineers, reliability engineers, data scientists, and data engineers. Novelis is advancing toward its vision of a “plant of the future” and has increased its responsiveness to customer demand, boosting customer satisfaction. The company’s strategic foresight has not only integrated predictive capabilities into its systems but has also facilitated a culture of innovation, proactive problem-solving, and continuous improvement.
Testimonial
Novelis Head of AI and Simulation Chirag Agrawal highlighted, “Novelis chose SymphonyAI Predictive Asset Intelligence due to its comprehensive AI capabilities, built-in domain expertise, and unified industrial data platform. SymphonyAI’s ability to integrate different data sources, apply both physics-based and ML approaches, and build AI insights into our existing workflows has helped us foster a collaborative environment, maximize the impact of predictive maintenance, and create a culture of innovation and efficiency.”
