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:

• Learn how New Zealand Steel, as the country's only steel maker, implemented predictive maintenance technology to enhance their unique iron sand-to-steel manufacturing process

• Discover how a strategic pilot program and robust data foundation helped build trust and drive successful adoption of predictive maintenance across the organization

• Understand how early detection of equipment issues, like loose gearbox mounting bolts, helped avoid 12 hours of critical downtime and potential catastrophic failures

• Explore how automation and standardization of configurations helped scale the implementation from 300 to a target of 3,000-5,000 assets while maintaining quality

• Learn about the multiple benefits beyond just downtime prevention, including quality improvements, yield optimization, and how proper data governance enables future digital transformation initiatives.

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