Data Driven Model Deployment in Manufacturing (Pilot)

SUMMARY

Deploying data-driven models in manufacturing isn’t just about building complex algorithms — it’s about making sure they work in the real world. In this lesson, we provide a high-level framework for successfully implementing these models to address manufacturing challenges.

We’ll explore the key steps, from data preparation and model integration to monitoring and continuous improvement. You’ll also learn how to overcome deployment challenges, like integrating models with legacy systems and scaling them for operational environments. Real-world examples will help you see how these techniques come to life in manufacturing operations. Whether you’re a beginner or someone already familiar with data-driven solutions, this lesson will help you unlock new efficiencies and optimize decision-making across the supply chain.

About The Author

Dilek Dustegor is a Professor of Computing Science at the University of Groningen in the Netherlands. She is interested in bridging the gaps between research, development and implementation using AI and automation. She is pursuing research about modeling, design and analysis of large scale / networked systems using IoT and ML techniques, with a special interest in smart city applications. She is a seasoned educator, and loves using the newest educational technologies for an enhanced learning experience.