Bibliographic Details
| Title: |
Modelling the influence of UV curing strategies for optimisation of inkjet based 3D printing |
| Authors: |
Peng Zhao, Yinfeng He, Gustavo F. Trindade, Martin Baumers, Derek J. Irvine, Richard J.M. Hague, Ian A. Ashcroft, Ricky D. Wildman |
| Source: |
Materials & Design, Vol 208, Iss , Pp 109889- (2021) |
| Publisher Information: |
Elsevier, 2021. |
| Publication Year: |
2021 |
| Collection: |
LCC:Materials of engineering and construction. Mechanics of materials |
| Subject Terms: |
Additive manufacturing, Inkjet printing, Polymerisation, UV light, Modelling, Optimisation, Materials of engineering and construction. Mechanics of materials, TA401-492 |
| More Details: |
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. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
0264-1275 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S0264127521004421; https://doaj.org/toc/0264-1275 |
| DOI: |
10.1016/j.matdes.2021.109889 |
| Access URL: |
https://doaj.org/article/424e380c7fb64182b6dad6dfe483a64a |
| Accession Number: |
edsdoj.424e380c7fb64182b6dad6dfe483a64a |
| Database: |
Directory of Open Access Journals |
