Self-Driven Process Optimization in Pneumatic 3D Printing: From Static Ensemble Learning to Autonomous Bayesian Method

Maxime Goulet, Audrey Laventure

Submission Type: I want my submission to be considered for both oral and poster presentation.

Keywords: Bayesian Optimization, Pneumatic Extrusion, Additive Manufacturing, Autonomous Manufacturing, Machine Learning, Polymers, Process Parameter Optimization

TL;DR: We present an open-source pneumatic printer that uses Bayesian optimization to autonomously self-tune processing parameters for materials ranging from liquid solutions to viscous melts.

Confirmation Of Submission Requirements: I submit an abstract. It uses the template provided on the submission page and is no longer than 2 pages.

Submission Number: 70