Applying AI to Predictive Maintenance at Scale: A Senseye Perspective

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 special
episode with David Humphrey, Director of Research, ARC Europe, we
discuss:How predictive maintenance has evolved from scheduled
inspections to data‑driven decision‑making using connected machine
data.What Senseye Predictive Maintenance is, how it works as a
cloud‑based analytics application, and where it fits within
Siemens’ broader asset and maintenance portfolio.How machine
learning and generative AI are used to detect abnormal asset
behavior and translate complex analytics into actionable
maintenance guidance.How historical machine data, maintenance
records, and technical documentation are leveraged to speed
diagnosis and reduce dependency on individual expert knowledge.Why
scalability, usability, and organizational adoption are critical
success factors for predictive maintenance programs operating at
hundreds or thousands of assets.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