Enhancement of High-Resolution 3D Inkjet-Printing of Optical Freeform Surfaces Using Digital Twins.

3D inkjet-printing additive manufacturing digital twin freeform optics modeling simulation varifocal optics

Journal

Micromachines
ISSN: 2072-666X
Titre abrégé: Micromachines (Basel)
Pays: Switzerland
ID NLM: 101640903

Informations de publication

Date de publication:
30 Dec 2020
Historique:
received: 30 11 2020
revised: 23 12 2020
accepted: 25 12 2020
entrez: 5 1 2021
pubmed: 6 1 2021
medline: 6 1 2021
Statut: epublish

Résumé

3D-inkjet-printing is just beginning to take off in the optical field. Advantages of this technique include its fast and cost-efficient fabrication without tooling costs. However, there are still obstacles preventing 3D inkjet-printing from a broad usage in optics, e.g., insufficient form fidelity. In this article, we present the formulation of a digital twin by the enhancement of an optical model by integrating geometrical measurement data. This approach strengthens the high-precision 3D printing process to fulfil optical precision requirements. A process flow between the design of freeform components, fabrication by inkjet printing, the geometrical measurement of the fabricated optical surface, and the feedback of the measurement data into the simulation model was developed, and its interfaces were defined. The evaluation of the measurements allowed for the adaptation of the printing process to compensate for process errors and tolerances. Furthermore, the performance of the manufactured component was simulated and compared with the nominal performance, and the enhanced model could be used for sensitivity analysis. The method was applied to a highly complex helical surface that allowed for the adjustment of the optical power by rotation. We show that sensitivity analysis could be used to define acceptable tolerance budgets of the process.

Identifiants

pubmed: 33396871
pii: mi12010035
doi: 10.3390/mi12010035
pmc: PMC7824045
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Helmholtz-Gemeinschaft
ID : POF 3, Science and Technology of Nanosystems

Références

Micromachines (Basel). 2016 May 06;7(5):
pubmed: 30404260
Opt Express. 2015 Nov 16;23(23):30438-47
pubmed: 26698523
Polymers (Basel). 2018 Nov 16;10(11):
pubmed: 30961203
Opt Express. 2010 Sep 27;18(20):20926-38
pubmed: 20940988
Polymers (Basel). 2018 Aug 18;10(8):
pubmed: 30960850
Polymers (Basel). 2019 Mar 05;11(3):
pubmed: 30960404
Appl Opt. 2013 Jul 20;52(21):5221-9
pubmed: 23872770
Polymers (Basel). 2018 Aug 06;10(8):
pubmed: 30960800
Opt Express. 2006 Aug 21;14(17):7757-75
pubmed: 19529146
Appl Opt. 2016 Aug 20;55(24):6671-9
pubmed: 27556988
Appl Opt. 2014 Jul 1;53(19):4248-55
pubmed: 25089987
Polymers (Basel). 2018 Nov 25;10(12):
pubmed: 30961229
Opt Express. 2020 Apr 27;28(9):13423-13431
pubmed: 32403817

Auteurs

Ingo Sieber (I)

Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany.

Richard Thelen (R)

Institute of Microstructure Technology-KNMF, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany.

Ulrich Gengenbach (U)

Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany.

Classifications MeSH