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When a Small Vibration Signal Prevents a Major Failure - with Emily Trott
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, we’re joined by Emily Trott from BlueScope Steel to unpack a real-world predictive maintenance success case, where a single vibration sensor helped prevent a critical failure before it happened.
It’s a practical, end-to-end story of how AI, engineering expertise, and process come together to move from early signal to real intervention — and how that translates into avoided downtime and operational impact.
What you’ll learn in this episode:
How a small vibration signal led to the discovery of a hidden failure on a connected asset
Why predictive maintenance is not one alert → one fix, but a multi-step investigation involving both AI and human expertise
The gap between traditional monitoring and predictive maintenance and why most failures are only detected when it’s already too late
How combining Senseye insights with on-site expertise changes the outcome from reactive to controlled intervention
Why sharing success cases internally is key to driving adoption, scaling, and new use cases across sites
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
To find out more about Bluescope Steel's approach to asset intelligence, please watch the video below:
https://www.youtube.com/watch?v=0dnDST5B1V4
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By SiemensWelcome 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, we’re joined by Emily Trott from BlueScope Steel to unpack a real-world predictive maintenance success case, where a single vibration sensor helped prevent a critical failure before it happened.
It’s a practical, end-to-end story of how AI, engineering expertise, and process come together to move from early signal to real intervention — and how that translates into avoided downtime and operational impact.
What you’ll learn in this episode:
How a small vibration signal led to the discovery of a hidden failure on a connected asset
Why predictive maintenance is not one alert → one fix, but a multi-step investigation involving both AI and human expertise
The gap between traditional monitoring and predictive maintenance and why most failures are only detected when it’s already too late
How combining Senseye insights with on-site expertise changes the outcome from reactive to controlled intervention
Why sharing success cases internally is key to driving adoption, scaling, and new use cases across sites
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
To find out more about Bluescope Steel's approach to asset intelligence, please watch the video below:
https://www.youtube.com/watch?v=0dnDST5B1V4