Understanding predictive maintenance buzzwords - with Maria Thoms

Welcome to the Trend Detection podcast, brought to you by Senseye
Predictive Maintenance – the platform which enables predictive
maintenance at scale across all of your assets, across all of your
plants.This episode covers:The Basics of Predictive Maintenance:
Understand how predictive maintenance uses data to forecast machine
failures and optimize maintenance schedules, saving time and
resources.AI and Machine Learning in Maintenance: Learn how AI and
machine learning algorithms analyze data to detect anomalies and
predict equipment breakdowns.Condition Monitoring as a Foundation:
Discover how condition monitoring collects real-time data to enable
predictive maintenance, providing insights into equipment
performance.Digital Twins Explained: Explore the concept of digital
twins—virtual models of physical assets—and how they help simulate,
test, and optimize machinery before real-world deployment.Cloud vs.
On-Premise Data Solutions: Understand the differences between cloud
and on-premise storage, focusing on security, accessibility, and
scalability for industrial applications.You can find out more about
how Senseye Predictive Maintenance can reduce unplanned downtime
and contribute towards improved sustainability within your
manufacturing plants, by visiting:
www.siemens.com/senseye-predictive-maintenance