Case Study: Global Manufacturing Company achieves scalable predictive maintenance and improved product reliability with Software AG

Smarter Manufacturing, Predictive Maintenance and Quality Control

A global industrial manufacturer with more than $60 billion in revenue across coatings, aerospace, automotive, electronics and energy faced escalating data complexity as it digitalized. Massive IoT sensor streams, multi-industry product portfolios, strict quality and liability requirements, and a small team relying on manually coded models created scalability bottlenecks, human-error risk, and an inability to achieve real-time processing.

The company implemented Software AG’s Zementis Predictive Analytics — a platform-agnostic solution for streaming IoT data — to operationalize and scale predictive models across organizations. This delivered real-time (and predictive) maintenance and quality control, lower costs, faster component development, improved product reliability (notably reduced bearing rework and unplanned downtime), and company-wide efficiency and post-sale support gains.