Understanding predictive maintenance buzzwords – with Maria Thoms [Video]

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:

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The Basics of Predictive Maintenance: Understand how predictive maintenance uses data to forecast machine failures and optimize maintenance schedules, saving time and resources.

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AI and Machine Learning in Maintenance: Learn how AI and machine learning algorithms analyze data to detect anomalies and predict equipment breakdowns.

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Condition Monitoring as a Foundation: Discover how condition monitoring collects real-time data to enable predictive maintenance, providing insights into equipment performance.

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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.

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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 (http://www.siemens.com/senseye-predictive-maintenance)