AM2PM: Additive to Predictive Manufacturing for Multistorey Construction Using Learning by Printing and Networked Robotics
Published July 4, 2025 | Version v1
Conference paper Open

Data-Driven Parameter Calibration in Additive Manufacturing for Construction: An Introduction to Learning by Printing

Authors/Creators

  • 1. ROR icon Technical University of Munich

Description

This paper presents the Learning by Printing framework, a data-driven, closed-loop system using Fabrication Information Modeling to optimize extrusion-based additive manufacturing in construction, achieving over 95% prediction accuracy and improved performance through parameter calibration.

Files

Data-Driven+Parameter+Calibration+in+Additive+Manufacturing.pdf

Files (1.7 MB)

Additional details

Funding

European Commission
AM2PM - ADDITIVE TO PREDICTIVE MANUFACTURING FOR MULTISTOREY CONSTRUCTION USING LEARNING BY PRINTING AND NETWORKED ROBOTICS 101162318