Zeppelin Takes Predictive Maintenance
to New Heights
with Splunk


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Predictive maintenance is one of the most promising uses of the industrial Internet of Things (IoT) today. The ultimate goal of most industrial organizations is to avoid costly repairs while improving the ability to maximize the availability of their equipment. Whether you are looking to improve efficiencies in production, maintenance, or operations, predictive capabilities are now within reach with machine learning.

Zeppelin, a large German holding company with a significant power division, wanted to uncover equipment issues before machine failure to ensure their customers didn’t suffer plant downtime. In this webinar, hear directly from key Zeppelin stakeholders about their initial challenge and how they are leveraging Splunk for data on-boarding, visualization and predictive analytics of critical equipment with machine learning.

Speaker 1
Rene Ahlgrim
Manager, Data Analytics
Zeppelin GmbH

Speaker 2
Andreas Zientek
Systems Engineer
Zeppelin GmbH
Speaker 3
Phillipp Drieger
Staff ML Architect
Splunk Inc.