Throwing it back to the FME AI for Industry Year event held last week. An insightful event where our Competence Lead Data Science, Ionuț Barbu, held a talk focusing on “Product Quality Prediction through Data & AI”. He shared our approach for Yield, Energy, Throughput (YET) optimization of manufacturing assets.

The presentation was well received. It addressed the challenge of insufficient proactive mitigation of quality defects and waste reduction. Ionuț delved deeper into the matter by presenting a concrete use case for product quality prediction. It featured a demonstrator dashboard for sensor data deep dives and identification of drivers of product quality. We had a notable discussion about our approach to embed expert process knowledge in feature engineering for machine learning models. More specifically, how can we find relationships between process parameter behavior and high/low quality products. 💡

Thanks to the FME for organizing this yearly event and to everyone who attended our session for their attention, questions, and lively discussions.

Let’s keep the conversation going! Drop Ionuț Barbu of Mart Althuizen a message for your specific challenge at hand. We are here to help! 🚀

🌐 Discover the impact we create for our clients here: