Hands-On with AI: Bringing Senseye to the Classroom- 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.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