Additive Manufacturing

3D Printing with Drones

What if a drone could build structures humans can't reach? We investigate integrating underactuated multicopters with 3D printing for large-scale remote additive manufacturing — demonstrating aerial positioning accuracy competitive with ground-based …

On the Feasibility of 3D Printing with Multicopters

In recent years, large-scale and fully-remote 3D printing with robots has garnered significant interest in construction applications. Combining the design freedom of 3D printing with a robot's versatility offers unique and promising opportunities for …

Towards Online Monitoring and Data-Driven Control: A Study of Segmentation Algorithms for Laser Powder Bed Fusion Processes

An increasing number of laser powder bed fusion machines use off-axis infrared cameras to improve online moni- toring and data-driven control capabilities. However, there is still a severe lack of algorithmic solutions to properly process the …

Geometrical Analysis of Simple Contours Deposited by a 3D Printing Hexacopter

Current limitations in vertical and horizontal mobility for ground robots in 3D printing of medium to large-scale objects have recently led to the development of a 3D printing hexacopter testbed at the University of Texas at Austin. This testbed can …

A 3D Printing Hexacopter: Design and Demonstration

3D printing using robots has garnered significant interest in manufacturing and construction in recent years. A robot's versatility paired with the design freedom of 3D printing offers promising opportunities for how parts and structures are built in …

GAIN Mechanical Engineering Department Award 2021

Awardee of the Mechanical Engineering Department Award for the 2021 Graduate and Industry Networking Event by the University of Texas at Austin for outstanding research.

An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing

We present a novel unsupervised deep learning approach that utilizes an encoder-decoder architecture for detecting anomalies in sequential sensor data collected during industrial manufacturing. Our approach is designed to not only detect whether …

First 3D Printing Attempt with a Drone

Unstable flight, premature extrusion, material that refuses to adhere — this is what aerial 3D printing looks like at the start. We document the first prototype test of a multi-year aerial additive manufacturing research program, including what went …

Predictive Iterative Learning Control with Data-Driven Model for Optimal Laser Power in Selective Laser Sintering

Building high quality parts is still a key challenge for Selective Laser Sintering machines today due to a lack of sufficient process control. In order to improve process control, we propose a Predictive Iterative Learning Control (PILC) controller …

Won Sandia National Laboratories Grant

Pitched and secured five-figure funding from Sandia National Labs for a novel laser pre-scan process that enhances part quality in selective laser sintering (3D printing).