Uploaded September 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 we're joined by Andrew Rehm, Director of Reliability and Planning at Highland Pellets, to explore how predictive maintenance is transforming industrial operations.
Andrew shares Highland Pellets' journey from traditional inspection-based maintenance to a more proactive, data-driven approach powered by AI. We discuss how the company increased plant uptime from 60% to 89%, uncovered critical issues before they became failures, and built trust in predictive maintenance across operations, maintenance, and reliability teams.
The conversation goes beyond technology, covering change management, workforce adoption, maintenance planning, and why predictive maintenance is becoming a core part of Highland Pellets' long-term strategy.
In this episode you will learn:
•
Why predictive maintenance looks very different today than it did ten years ago
•
How Highland Pellets identified the right assets to monitor first
•
The story behind a critical failure that was detected before it shut down production
•
Moving from scheduled inspections to condition-based maintenance
•
Building trust in AI-driven insights among maintenance teams
•
Connecting predictive maintenance with CMMS workflows and planning processes
•
Lessons learned from the first deployment and plans to scale further
•
Why the future of maintenance is data-driven, proactive, and predictive
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 we're joined by Andrew Rehm, Director of Reliability and Planning at Highland Pellets, to explore how predictive maintenance is transforming industrial operations.
Andrew shares Highland Pellets' journey from traditional inspection-based maintenance to a more proactive, data-driven approach powered by AI. We discuss how the company increased plant uptime from 60% to 89%, uncovered critical issues before they became failures, and built trust in predictive maintenance across operations, maintenance, and reliability teams.
The conversation goes beyond technology, covering change management, workforce adoption, maintenance planning, and why predictive maintenance is becoming a core part of Highland Pellets' long-term strategy.
In this episode you will learn:
•
Why predictive maintenance looks very different today than it did ten years ago
•
How Highland Pellets identified the right assets to monitor first
•
The story behind a critical failure that was detected before it shut down production
•
Moving from scheduled inspections to condition-based maintenance
•
Building trust in AI-driven insights among maintenance teams
•
Connecting predictive maintenance with CMMS workflows and planning processes
•
Lessons learned from the first deployment and plans to scale further
•
Why the future of maintenance is data-driven, proactive, and predictive
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)
