A Mobile Additive Manufacturing Robot Framework for Smart Manufacturing Systems

TL;DR

This paper introduces a mobile additive manufacturing robot framework that enhances manufacturing flexibility and throughput by integrating autonomous mobility with 3D printing, especially useful for remote or on-demand production scenarios.

Contribution

It presents a novel framework combining additive manufacturing with autonomous mobile robots, demonstrated through case studies showing increased throughput and operational flexibility.

Findings

Mobile AM robots increase throughput by utilizing travel time.

The framework is effective for intermittent operations like feedstock preparation.

Applicable in remote or extreme terrain manufacturing environments.

Abstract

Recent technological innovations in the areas of additive manufacturing and collaborative robotics have paved the way toward realizing the concept of on-demand, personalized production on the shop floor. Additive manufacturing process can provide the capability of printing highly customized parts based on various customer requirements. Autonomous, mobile systems provide the flexibility to move custom parts around the shop floor to various manufacturing operations, as needed by product requirements. In this work, we proposed a mobile additive manufacturing robot framework for merging an additive manufacturing process system with an autonomous mobile base. Two case studies showcase the potential benefits of the proposed mobile additive manufacturing framework. The first case study overviews the effect that a mobile system can have on a fused deposition modeling process. The second case study showcases how integrating a mobile additive manufacturing machine can improve the throughput of the manufacturing system. The major findings of this study are that the proposed mobile robotic AM has increased throughput by taking advantage of the travel time between operations/processing sites. It is particularly suited to perform intermittent operations (e.g., preparing feedstock) during the travel time of the robotic AM. One major implication of this study is its application in manufacturing structural components (e.g., concrete construction, and feedstock preparation during reconnaissance missions) in remote or extreme terrains with on-site or on-demand feedstocks.