Industry: Telecom, Media and Technology
Region: Northern America
Avoiding operational downtime while lowering costs and improving visitor satisfaction with an advanced predictive maintenance solution
As a standard-bearer for its industry, a major media and theme park operator is dedicated to surprising and delighting visitors all over the world.
So, when one of its popular attractions is out of service, this has a negative effect on customer satisfaction. What’s more, operational challenges can arise from the disruption; and revenues are reduced when visitors can’t reach the rides and outlets they’d like.
Existing sensors on rides would enable the company to gather high volumes of detailed data on the operational status of each attraction. The real challenge was how to harness all that data and turn it into accurate insights that could be quickly and efficiently actioned by the company’s maintenance crew.
Atos developed a high-speed streaming data analytics platform that processes around 180 billion data points every hour.
Data passes through multiple artificial intelligence (AI) models to alert engineers of any downtime up to 30 days in advance. With enhanced compute power and storage, state-of-the-art BullSequana S servers and BullSequana Edge devices keep data secure and processing in real-time.
Maintenance procedures have fundamentally shifted, leading to less downtime, lower costs and happier visitors.
The company can eliminate inefficient preventive maintenance and carry out more highly targeted predictive maintenance. The maintenance crews’ interactive dashboards give them unprecedented access to real-time and historical data to help them diagnose and repair any problems fast.
The team is also exploring more ways to leverage the platform beyond attractions, such as safety and vehicle flow around the parks.
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Head of TMT Alliances & Media Portfolio