Creative Thinking in Predictive Maintenance: A Conversation with Jordan Walters

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.This episode
covers:The Essence of Creativity in Engineering: How creative
thinking is crucial for innovating solutions to complex problems in
predictive maintenance (PM), moving beyond established methods to
develop bespoke approaches for each customer.Unconventional
Problem-Solving with Existing Tools: Discover how seemingly limited
data, like temperature readings from electric car charger pins, can
be creatively manipulated using features like "derived measures" to
detect degradation, even when traditional sensor deployment isn't
feasible.Bridging the Gap: From Industrial Practice to Education:
Learn about the "Connected Curriculum" initiative, which brings
Senseye to university students, and the creative adaptations needed
to teach real-world data challenges (like noisy or incomplete data)
and PM principles in an academic setting.Debunking Misconceptions
about AI and Data: Understand that perfect data is a myth and that
effective AI in PM, like Senseye, thrives on curated, clean data
focused on specific condition indicators, rather than a "big data"
dump, to provide nuanced and accurate insights.AI as an Enabler for
Human Creativity: Explore how AI serves as a powerful tool to
support and amplify human ingenuity in engineering, emphasizing the
importance of asking questions, providing context, and fostering a
collaborative environment to drive innovation and personal growth
in the field.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