Implement PdM correctly: Best practices, tools & practical examples

Hey guys!
Hope each one of you is doing well.
I'd like to welcome all of you to our first meetup this year :)!

Our special guest will be Dr. Benjamin Adrian who will among other details give us an insight into Fraunhofer's various projects involving Predictive Maintenance systems.

I am looking forward to see you all again and have an interesting discussion.

Cheers and see you online on the 23rd at 6PM! :)
Selma

Abstract:
"Predictive maintenance" is a popular buzzword when it comes to launching digitization projects in maintenance and production. From a maintenance perspective, predictive maintenance is the optimal strategy for condition-based planning of maintenance windows. From the production point of view, the underlying "condition monitoring" offers the lot-based calculation of the wear stock of involved production processes.

In this presentation, we will give an insight into various projects in which we have set up concrete "Predictive Maintenance" systems with customers. Despite the high degree of individuality of each plant, we present a proven overarching approach and show tools that help us build predictive maintenance systems for complex and individual plants.

Speaker Bio:
Dr. Benjamin Adrian studied applied computer science at the Technical University of Kaiserslautern. After completing his doctorate at the German Research Center for Artificial Intelligence, Dr. Adrian worked first at "Insiders Technologies GmbH", then at "Empolis Information Management GmbH" in product development and product management, where he was responsible for the development of AI-based software systems for the automation of service processes. Due to the rapid development of machine learning in maintenance and production processes, he returned to applied research to implement projects and especially complete systems for "Condition Monitoring" and "Predictive Maintenance" at the "Fraunhofer Institute for Industrial Mathematics (ITWM)" in the team of the department "System Analysis, Prognosis and Control" for and together with industrial customers.

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