Optical form measurement of complex rough surfaces to improve the precision of additive manufactured parts
Funding: H2020 Marie Skłodowska-Curie Actions - Innovative Training Networks (ITN)
Duration: June 2017 – June 2020
PhD Student: Amrozia Shaheen
Supervisors: Richard Leach, Petros Stavroulakis
Website: https://www.pam2.eu/
The aim of this project is to revisit existing state-of-the-art optical 3D form measurement methodologies such as photogrammetry, laser scanning and fringe projection (shown in Figure 1). For the most appropriate methodology, research will be carried out to improve the measurement pipeline starting from the optics, all the way to the algorithms used, with the goal of enabling the fast, easy and efficient assessment of metal additive manufactured (AM) objects after they have been manufactured. More specifically, the project will focus on the development of an appropriate mathematical model for the effect of the optical design to the quality of the 3D points measured, along with the study of the optical interaction of existing equipment with metal AM surfaces. This will lead to the creation of a setup with an optimal optical transfer function for the measurement of complex AM objects. With regards to optimising and accelerating existing 3D measurement algorithms, the project will leverage the use of a priori knowledge and the CAD model of the object in an information-rich metrology framework, which is a core competency of the Manufacturing Metrology Team (MMT) at the University of Nottingham.
The practical demonstration and characterization of the proposed theoretical model is needed to address practical concerns, such as systematic errors and environmental noise issues, which would affect the optical and image processing techniques. The ultimate goal of MMT is to use the accurate optical measurement results to provide quality control feedback to the AM manufacturing process and, as a result, improve its accuracy, speed and precision.
Precision Additive Metal Manufacturing (PAM2) is a Marie Skłodowska-Curie Innovative Training Network (ITN) funded by the European Union under the Horizon 2020 Programme. PAM2 has close collaboration with industry and academia to address the quality assurance and the various process stages of AM, with the aim of implementing good precision engineering practice.
The fringe projection setup in the MMT form lab.