Case Study: Zeppelin achieves predictive maintenance and higher uptime with Splunk

Zeppelin improves equipment uptime and analyzes thousands of IoT logs with Splunk

Zeppelin, a German manufacturer specializing in construction and rental machinery, needed to reduce downtime and scale its services business by monitoring rental equipment remotely. The company required a solution to analyze sensor data for predictive maintenance and to gain a comprehensive view of its complex IT infrastructure. To meet this challenge, Zeppelin turned to Splunk and implemented Splunk Enterprise.

Using Splunk Enterprise and the Splunk MLTK, Zeppelin implemented predictive maintenance to analyze data from thousands of IoT devices. This solution allowed them to predict failures, such as spark plug issues in engines, and dispatch technicians before a breakdown occurred. As a result, Splunk helped Zeppelin accelerate troubleshooting, increase equipment uptime for customers, improve customer satisfaction, and prevent costly shutdowns.

Zeppelin