Case Study: World Leading Theme Park Operating Company achieves reduced downtime and higher visitor satisfaction with Atos predictive maintenance solution

Avoiding operational downtime while lowering costs and improving visitor satisfaction with an advanced predictive maintenance solution

World Leading Theme Park Operating Company, a global leader in media and attractions, needed to stop popular rides from unexpectedly going out of service—an issue that hurt visitor satisfaction, operations and revenue. Already collecting high-volume sensor data, the company wanted to move from costly preventive maintenance to a real‑time, predictive approach and asked Atos for a solution.

Atos delivered a high‑speed streaming data analytics platform (processing ~180 billion data points per hour) that uses multiple AI models, BullSequana S servers and BullSequana Edge devices, and mobile dashboards to alert engineers up to 30 days in advance. The Atos solution shifted maintenance from blanket preventive work to targeted predictive fixes, reducing downtime and costs, speeding diagnosis and remediation, improving visitor satisfaction, and providing a scalable platform for other parks and cruise lines.