CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume PC12939 > Article
Presentation
11 April 2024 A machine-learning approach for reliable process parameter prediction in three-dimensional additive microprinting
Georg von Freymann, Julian Hering, Svenn Enns, Nicolas Lang
Author Affiliations +
Proceedings Volume PC12939, High-Power Laser Ablation VIII; PC129390Z (2024) https://doi.org/10.1117/12.3014314
Event: SPIE High-Power Laser Ablation, 2024, Santa Fe, New Mexico, United States
Abstract
Three-dimensional microprinting via two-photon absorption is the additive manufacturing technique of choice for complex micro-optical systems. Since post-processing of printed micro-optics is not possible in most cases, deviations between design and printed samples affect the intended function and therefore need to be minimized. This is a difficult task since important material properties such as shrinkage and refractive index depend on the cross-linking density and thus on the process parameters. We present first results towards a detailed prediction of 3D printed structures based on a modeling approach combined with machine learning to adjust the corresponding process parameters.
Conference Presentation
© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Georg von Freymann, Julian Hering, Svenn Enns, and Nicolas Lang "A machine-learning approach for reliable process parameter prediction in three-dimensional additive microprinting", Proc. SPIE PC12939, High-Power Laser Ablation VIII, PC129390Z (11 April 2024); https://doi.org/10.1117/12.3014314
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 PRESENTATION
WATCH
PRESENTATION SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
KEYWORDS
Machine learning
Printing
Additive manufacturing
Complex systems
Design and modelling
Materials properties
Micro optics
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top