Development and Application of Chemical Sensing Technology for Additive Manufacturing

Lead Research Organisation: University College London
Department Name: Mechanical Engineering

Abstract

Additive manufacturing (AM) is an advanced manufacturing technology that converts digital designs into complex structures with functional properties for a variety of industrial applications, including aerospace, biomedical, and fusion. Laser powder bed fusion (LPBF) is a form of AM that uses a laser beam to fuse a thin powder and its supporting substrate, forming sequential melt pools which are then solidified into desired shapes. The intense laser energy delivered to form the melt pool can induce a plume at the interaction zone, forming undesirable features (e.g. porosity and cracks) and compositional variations in the component, both of which can be detrimental to the product quality and performance.
Traditional in situ monitoring captures aspects of the process dynamics but does not provide sufficient information to explain the laser-plume interaction and its impact during LPBF. Therefore, the underlying physical understanding behind the laser-plume dynamics remains unclear. In this project, we will design, build, and employ a chemical sensing instrument for AM that enables the detection and analysis of the plume chemistry during LPBF. The development of such a chemical sensing instrument (including software and hardware) for AM would require a high signal-to-noise ratio, temporal resolution, and long-term operational stability. This instrument will enable monitoring of the plume dynamics during printing, aim to minimise the compositional variations in the AM parts, and deduce optimum parameters to form melt pools without plume generation, ultimately improving the productivity of the AM process.
This multidisciplinary research project will combine the capabilities in the supervisors' groups in instrument design, additive manufacturing, machine-learning, spectroscopy, signal, and image processing. The project will also offer an opportunity to extend to a PhD with the ultimate goal to integrate the chemical sensing system to a commercial AM system, demonstrating its impact in an industrial context.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509577/1 01/10/2016 24/03/2022
2453539 Studentship EP/N509577/1 26/10/2020 25/01/2025 Anna Getley