Uploaded August 2026 | Updated September 2026, 2 weeks ago
Welcome to the Trend Detection podcast, brought to you by Senseye Predictive Maintenance – which gives you visibility and insights into all your assets, from single machines to full plants to help you reduce downtime, increase knowledge sharing and accelerate digital transformation across your organization.
In this episode of the Trend Detection Podcast, Niall Sullivan is joined by Chris Smith, Head of Operations for Senseye Predictive Maintenance, to explore the relationship between predictive maintenance and computerized maintenance management systems, or CMMS.
Chris explains why organizations should consider establishing value and learning how predictive maintenance fits within their operations before fully integrating it into existing workflows. He also discusses how CMMS data can provide valuable context, reduce manual investigation and help maintenance teams focus their attention on the issues that require action.
In this episode, you’ll learn:
•
When to integrate predictive maintenance with your CMMS
•
How CMMS data adds context and accelerates decision-making
•
Why trust and ownership matter more than technology alone
•
How to turn predictive insights into maintenance action
•
Why standardised integrations still require local flexibility
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: siemens.com/senseye-predictive-maintenance (siemens.com/senseye-predictive-maintenance)
Welcome to the Trend Detection podcast, brought to you by Senseye Predictive Maintenance – which gives you visibility and insights into all your assets, from single machines to full plants to help you reduce downtime, increase knowledge sharing and accelerate digital transformation across your organization.
In this episode of the Trend Detection Podcast, Niall Sullivan is joined by Chris Smith, Head of Operations for Senseye Predictive Maintenance, to explore the relationship between predictive maintenance and computerized maintenance management systems, or CMMS.
Chris explains why organizations should consider establishing value and learning how predictive maintenance fits within their operations before fully integrating it into existing workflows. He also discusses how CMMS data can provide valuable context, reduce manual investigation and help maintenance teams focus their attention on the issues that require action.
In this episode, you’ll learn:
•
When to integrate predictive maintenance with your CMMS
•
How CMMS data adds context and accelerates decision-making
•
Why trust and ownership matter more than technology alone
•
How to turn predictive insights into maintenance action
•
Why standardised integrations still require local flexibility
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: siemens.com/senseye-predictive-maintenance (siemens.com/senseye-predictive-maintenance)
