Description
- AI is not yet delivering on its big problem-solving promise because it lacks real-world context.
- In proactive maintenance, context is the info needed to go from change detected to action to resolve
- Bringing real-world context into digital systems is essential for AI to become truly effective.
- The end goal is a context-aware Analytic Solution that can reason, diagnose, and act with human-level intelligence
Biography
Dries holds an Electro-Mechanical engineering degree with specialization in maintenance, from the
University of Antwerp, Belgium. He has 10 years of experience in Predictive Maintenance
Dries started his working career at a predictive maintenance company actively using all existing predictive
technologies throughout various different industries. After a couple years, he joined PRUFTECNIK Benelux
as an application engineer getting involved in high-end troubleshooting using on and offline vibration
measurements. Soon he was made responsible for all online condition monitoring projects, from initial
design through installation and monitoring.
Beginning 2014 he moved to the US office of PRUFTECHNIK (now Fluke) to setup a condition monitoring
department to serve the US market on all CM related topics, including proactive maintenance, remote
(temporary) monitoring, trouble shooting and torque measurements.
In 2017 Dries had the opportunity to participate in the ISO CAT 4 Vibration class and passed the exam,
becoming one of the youngest CAT 4 analyst at that time.
Since the beginning of 2021, Dries has joined NanoPrecise a Start-up with a unique end to end wireless
condition monitoring solution, as the VP of Customer Success he is responsible for all customer success
as well as product roadmap.
