Trend Detection Podcast

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

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.

In this episode we revisit last years SPS to explore the state of readiness in the Danish Market.

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

Willkommen zum Trend Detection Podcast, präsentiert von Senseye Predictive Maintenance – der Plattform, die eine skalierbare vorausschauende Instandhaltung für sämtlicheAnlagen ermöglicht. 

Beschreibung:  • Die Entwicklung erkunden: Entdecken Sie die aktuellen Fortschritte in der industriellen KI und Automatisierung, während wir uns mit den neusten Tools und Technologien beschäftigen, die die Industrie prägen.  

• Die Revolution der Automatisierung: Entdecken Sie mehr über die zukunftsweisenden Projekte von Siemens, darunter das Copilot-System und digitale Geschäftsmodelle im Umfeld der Fabrikautomatisierung.  

• Einblicke in KI-Strategien: Erfahren Sie mehr über vorausschauende Instandhaltung, KI-Infrastrukturen und wie generative KI die Industrie verändert. 

 • Zukünftige Trends: Werfen Sie einen Blick in die Zukunft der industriellen KI, einschließlich aufkommender Technologien und zukünftiger Veränderungen in der Industrie.. 

Weitere Informationen darüber, wie Senseye Predictive Maintenance ungeplante Ausfälle reduziert und die Nachhaltigkeit Ihrer Produktionsanlagen verbessert, finden Sie unter www.siemens.com/senseye-predictive-maintenance 

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:

• Overview of the deployment of Senseye Predictive Maintenance deployment at Bluescope Steel

• Deep dive into a success case that resulted in 24 hours unplanned downtime savings

• How the new copilot functionality in Senseye is transforming the way they work

• Advice to other companies looking to implement predictive maintenance solutions

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

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:

• Optimizing Plant Performance and Reducing Downtime

  • Learn how predictive maintenance uses data insights to improve efficiency, keep operations smooth, and minimize unplanned downtime.

• Enhancing Product Quality and Safety

  • Explore how early issue detection helps maintain consistent product quality, safeguards employees, and reduces environmental risks.

• Scalable Solutions for Proactive Issue Detection

  • Discover how our scalable predictive maintenance solutions enable you to detect potential issues before they occur, ensuring safer and more sustainable operations.

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

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 with Chris Garrison Covers:

• The Evolution of Predictive Maintenance and Sensor Technology: How advancements in sensor tools enable proactive fault prediction.

• Starting Predictive Maintenance with Available Data: Using onboard diagnostics to kickstart predictive maintenance without major investments.

• Optimizing Sensor Coverage for Different Equipment: Determining the right sensor setup based on equipment complexity and fault characteristics.

• Adopting a Holistic Approach to Asset Health: Leveraging diverse data types to gain a comprehensive view for proactive maintenance.

• Unlocking Benefits Beyond Maintenance: How predictive maintenance improves safety, reduces downtime, and enhances efficiency across the organization.

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

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.

Listen to learn how our Senseye Predictive Maintenance improves production and management KPIs by analyzing and predicting machine and maintainer behavior using AI – and you do not have to be data scientist!

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

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.

Listen to learn how our Senseye Predictive Maintenance improves production and management KPIs by analyzing and predicting machine and maintainer behavior using AI – and you do not have to be data scientist!

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

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.

Listen to learn how our Senseye Predictive Maintenance improves production and management KPIs by analyzing and predicting machine and maintainer behavior using AI – and you do not have to be data scientist!

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

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.

In this session, we discussed the following:

• The role of data analytics in predictive maintenance and how to harness its full potential.

• How to leverage human expertise alongside advanced algorithms to achieve a more proactive maintenance approach.

• Using GenAI (Generative Artificial Intelligence) to help prevent equipment failures.

• Real-world case studies showcasing successful implementations of Senseye Predictive Maintenance.

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