Mini symposium Predictive Maintenance & Condition Monitoring
News | May 27, 2024
Thursday afternoon, May 24, it was “Fullhouse” in the Idzerda hall of the SKILL building in Drachten. More than 70 experts in the field of Predictive Maintenance and Condition Monitoring attended.
In addition to the fact that the lectures were in both English and Dutch, there was also a large substantive variation in application of the field. From Philips (Daniel Caljouw) and the Greek company Atlantis (Naskos Thanassis) we zoomed in on the shaving cap production and the value that data can add to the improvement and maintenance of these processes.
XparVision (Sjoerd van der Zwaan) went into detail about their inspection systems for glass production. These systems provide handling and maintenance perspectives for operators, linked robots or in a closed loop with the entire glass production system.
Astron (Sorad Yatawatta) explained how they take sky photos and work with large amounts of data. The emphasis in this presentation was on system health monitoring to detect defective sensors and then disable them, so that the data produced remains pure.
C.G.I (Jan Willem Sytsma) once again emphasized the business side of this new applied AI domain under the banner of Industry 5.0. The main conclusion was that domain and AI knowledge is necessary for the sum of the parts to be greater, with domain knowledge increasingly coming into the AI domain.
The afternoon concluded with an interactive panel/room discussion. The central question was where the added value of this data-driven approach begins, and sometimes also ends. With assistance from Gerard van der Kolk (NHL Stenden) and Hendrik Jan Hoekstra (Firda) a second round was started on the role of human education and interaction with the increasingly smarter machine. The main conclusion was that companies should help knowledge institutions to develop this education, with or without AI.
This successful afternoon was provided by AI Hub Northern Netherlands, FME Northern region and the Innovation Cluster Drachten.