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Hybrid additive robotic workcell for autonomous fabrication of mechatronic systems - A case study of drone fabrication

Authors :
Tadeusz Kosmal
Kieran Beaumont
Eric Link
Dalton Phillips
Conner Pulling
Heather Wotton
Camille Kudrna
Joseph Kubalak
Christopher Williams
Source :
Additive Manufacturing Letters, Vol 3, Iss , Pp 100100- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

This paper presents the realization of a robotic workcell capable of autonomous, flexible, fabrication of complete, full-scale, functional mechatronic systems. Using a 6-DOF robotic arm with a hybrid Additive Manufacturing (AM)/Pick and Place (PnP) end effector, the workcell can rapidly print enclosures, insert and wire functional electronics, and embed them into the printed structure. The workcell's scalable control system, digital workflow for creating assembly instructions, hybrid AM/PnP toolhead design, and autonomous part tending mechanism are detailed. In addition, a modular electronics infrastructure is presented to enable facile, error-free robotic wiring of large-gauge copper wire. The workcell's ability to manufacture is verified in a case study wherein it is used to autonomously fabricate a variety of Unmanned Aerial Systems (UASs). In the study, the workcell produces a functional quadrotor drone, releases the drone from the workcell, and allows the drone to record the workcell constructing a second, different drone - all without human involvement. The resulting workcell, which combines digitally-integrated manufacturing, robotics and automation, and hybrid process manufacturing, enables autonomous manufacture of complete, functional mechatronic systems that are tailored to custom design needs in a just-in-time manner.

Details

Language :
English
ISSN :
27723690
Volume :
3
Issue :
100100-
Database :
Directory of Open Access Journals
Journal :
Additive Manufacturing Letters
Publication Type :
Academic Journal
Accession number :
edsdoj.99520ae8614e4236925d9bc2f10d836f
Document Type :
article
Full Text :
https://doi.org/10.1016/j.addlet.2022.100100