This PhD project aims to determine the possibilities for using BeamAssure™ beam characterisation, industrial camera footage and other quality assurance systems in the Industry 4.0 paradigm.
Electron beam welding (EBW) has the ability to produce joints with excellent integrity, therefore, it is used in industries requiring the most exacting standards and quality, e.g. aerospace and nuclear. In such applications, defective welds could lead to safety and infrastructure concerns.
The objective of this work is to analyse multiple input quality indicators to derive a quality assurance system. Research focuses on creating data-driven, real-time process health monitoring systems using artificial intelligence tools. The quality indicators examined will include BeamAssure signal processing, encoded time series data as images, image segmentation of data collected by cameras inside EB machines and data collected from process sensors.
It is anticipated that research outcomes could lead to higher weld integrity, better process monitoring and reduced failure rates in service.