This interactive workshop will serve as an exchange of experiences around the introduction and use of machine learning in manufacturing processes: the workshop moderator will relate to one specific case to kick-off the discussion, and the workshop participants are welcome to add their own personal experiences.
Together, we will discuss the implementation and benefits of different types of analytical models such as predictive quality and predictive maintenance to identify issues in the production process (e.g. to provide a “traffic light” to find out if the process is doing well or not).
A key element of this workshop is to move beyond predictive analytics to cover prescriptive analytics models to get the production process back on track, if it risks to miss the quality gates. Using this type of models the end users on the shop floor will get a recommendation of how to set up / modify the machine parameter settings.
Overall, the benefits of using such models in production are many-fold : 1) optimize the productions process (e.g. to reduce waste, reduce cost, support inexperienced workers) 2) gain experience with the use of machine learning technology in the production process and building up knowledge by bridging the gap between operations technology and IT / data science 3) secure manufacturing sites in Europe which are facing tough competition
Speaker: Dr. Georg Droschl (pmOne AG)