Machine learning in industrial systems

What it covers

This unit introduces you to the principles and applications of machine learning in industrial systems, with a focus on solving real-world engineering problems using data-driven approaches. As modern industries increasingly adopt intelligent and automated systems, machine learning has become a core enabling technology for enhancing efficiency, reliability, safety, and decision-making across manufacturing, infrastructure, energy, and process industries. You will explore the integration of fundamental industrial and machinery systems knowledge with introductory machine learning (ML) techniques. You will develop a foundational understanding of key machine learning methods, including supervised and unsupervised learning, feature extraction, model training, and performance evaluation. Through industry-motivated case studies, you will examine applications such as predictive maintenance, fault detection and diagnosis, quality inspection, condition monitoring, and process optimisation. By the end of the unit, you will be equipped with the skills to critically evaluate machine learning solutions and apply them effectively within industrial engineering contexts.

Assessment

When and where