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 assetWhy predictive
maintenance is not one alert one fix, but a multi-step
investigation involving both AI and human expertiseThe gap between
traditional monitoring and predictive maintenance and why most
failures are only detected when it’s already too lateHow combining
Senseye insights with on-site expertise changes the outcome from
reactive to controlled interventionWhy sharing success cases
internally is key to driving adoption, scaling, and new use cases
across sitesYou 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-maintenanceTo find out
more about Bluescope Steel's approach to asset intelligence, please
watch the video below:https://www.youtube.com/watch?v=0dnDST5B1V4