Predictive Maintenance Is Not the Strategy - A panel discussion

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. Moving from reactive maintenance to a more predictive approach sounds straightforward. In reality, technology is only one part of the equation. In this episode of Trend Detection, Niall Sullivan is joined by maintenance and asset management experts Kevin Clark, Corey Dickens, Rachel Green and Marc Trusio to explore what it really takes to build a more proactive maintenance strategy. They discuss: Why predictive maintenance should be part of a broader asset strategy, rather than the strategy itselft How manufacturers can move beyond reactive maintenance and escape “pilot purgatory” Why engaging maintenance teams early is critical to adoption and long-term success The value of predictive approaches beyond reducing downtime, from workforce confidence and knowledge capture to better planning and decision-making Why having more asset data doesn't automatically translate into better insights How manufacturers can make use of data from older and less connected equipment Where industrial AI can support maintenance teams, including identifying anomalies, capturing expertise and making knowledge more accessible Why people, culture and change management can ultimately determine whether new maintenance technologies succeed or stall Whether you're still largely reactive or already expanding predictive maintenance across your operations, this episode explores how to take the next step towards a more proactive, data-driven approach to 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