Modelling the influence of UV curing strategies for optimisation of inkjet based 3D printing

Zhao, Peng; He, Yinfeng; Trindade, Gustavo F.; Baumers, Martin; Irvine, Derek; Hague, Richard; Ashcroft, Ian; Wildman Conceptualisation, Ricky

Abstract

A predictive model is developed to assist in the design and manufacture of structures by inkjet based 3D printing (IJ3DP)/additive manufacturing. IJ3DP often exploits photopolymerisation to rapidly convert a photoreactive liquid ink into a solid product. Unfortunately, deviations from the intended design and product performance are often observed and a lack of understanding of the underlying processes and their interactions prevents users from resolving these issues. We develop and validate a predictive model that incorporates the critical processing parameters, including UV source pathway, UV intensity, printing strategy, and interlayer attenuation, such that we are able to predict the degree of ink conversion throughout the product. We show how this model can then be used to guide users by demonstrating the coupling of this description with a cost model and illustrating how printing strategy affects descriptors of both the quality and cost of production.

Citation

Zhao, P., He, Y., Trindade, G. F., Baumers, M., Irvine, D., Hague, R., Ashcroft, I., & Wildman Conceptualisation, R. (2021). Modelling the influence of UV curing strategies for optimisation of inkjet based 3D printing. Materials and Design, 208, Article 109889. https://doi.org/10.1016/j.matdes.2021.109889

• Journal Article Type: Article
• Acceptance Date: Jun 8, 2021
• Online Publication Date: Jun 10, 2021
• Publication Date: 2021-10
• Deposit Date: Jun 18, 2021
• Publicly Available Date: Jun 18, 2021
• Journal: Materials and Design
• Print ISSN: 0264-1275
• Electronic ISSN: 1873-4197
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 208
• Article Number: 109889
• DOI: https://doi.org/10.1016/j.matdes.2021.109889
• Keywords: Mechanical Engineering; General Materials Science; Mechanics of Materials
• Public URL: https://nottingham-repository.worktribe.com/output/5690774
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0264127521004421