Machine Learning for Industrial Processes

The core concept in Machine Learning (ML) is how to teach computers to learn from data. This implies that we must teach machines how to recall, adapt (or make adjustments), and generalize the information they have acquired in order for them to apply it to similar situations and cases. Machine Learning brings together ideas from neuroscience, physics, mathematics, statistics, and biology to enable computers to learn through modelling.

Machine Learning has gained increasing attention in industrial processes such as laser hardening, laser welding, grinding and additive manufacturing (AM) due to its high performance in data analysis tasks such as classification, regression and clustering. In the field of manufacturing processes, the various Machine Learning techniques can support the design, process control and production phases.

Laser Group's Machine Learning activities

Research into the applicability of Machine Learning to industrial processes is a growing field: Machine Learning is an efficient tool for data analysis and data mining, easily overcoming some of the limitations of experiments, high-precision simulations or in-situ monitoring systems in terms of time and cost, providing accurate, robust and rapid predictions with a flexible approach that fits a wide range of industrial problems.