On June 27, 2025, our former BIBA colleague Henry Ekwaro successfully completed his doctoral colloquium. His dissertation “A Systematic Evaluation of the Applicability of Machine Learning for Energy Efficient Manufacturing” was supervised by Prof. Klaus-Dieter Thoben, University of Bremen and Prof. Tobias Glasmachers, Institute for Neuroinformatics at the Ruhr University Bochum.

The work addresses an important and practice-relevant topic: While machine learning promises to improve manufacturing energy efficiency, knowing when and how to use it remains a critical barrier for the industry. This dissertation tackles this challenge by investigating the specific scenarios where ML provides real advantages over traditional methods. By systematically analyzing real-world datasets, this research uncovers the nuanced trade-offs between model performance, complexity, and data requirements. The core contribution is a novel methodology, implemented in an accessible low-code platform, that empowers both experts and novices to select the most effective models for their goals. This provides a clear roadmap for manufacturers to make informed decisions, harness their data, and advance sustainable operations.