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.

We are joined by Dr Aris Alexoulis from Manchester Metropolitan University and Jordan Walters and Steve Jones from Siemens to discuss:

• How Siemens’ Connected Curriculum equips students with real-world Industry 4.0 skills by integrating Senseye Predictive Maintenance into university teaching.

• The structure of the three-week pilot at MMU: from ingesting data to configuring anomalies, trends, and thresholds, giving students hands-on PdM experience.

• The role of Senseye Copilot in supporting learning—using natural language to explain alerts, provide context, and extend teaching beyond the classroom.

• The impact on students’ employability and career pathways, with predictive maintenance skills shaping projects and future opportunities.

• How academic feedback drives product improvements—such as simplifying derived measures—and helps refine training for both students and industry users.

• Next steps for the program: embedding the module at MMU, scaling to other universities, and building a distributed network of Festo labs for collaborative PdM monitoring.

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