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Closed-Loop Control by Laser Power Modulation in Direct Energy Deposition Additive Manufacturing

Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

Direct Energy Deposition is a metal additive manufacturing technique that has raised great interest in industry thanks to its potential to realize complex parts or repairing damaged ones, but the complexity of this process still requires much effort from practitioners to achieve functionally sound parts. One of the recurring flaws of such parts is the phenomenon of over-deposition, which may occur due to unpredicted local increases of energy density.

The deposition of uniform metal tracks is critical in many practical cases, when parts are composed by a significant number of layers and/or when complex tool paths induce heat build-up, for example in thin structures. Therefore, detecting anomalies such as over-growth in real-time and dynamically correcting them is of paramount importance for achieving repeatable, first-time-right parts.

This work studies the use of a closed-loop control system for Direct Energy Deposition, proposing to adjust on-line the power of the laser beam according to the feedback provided by the analysis of melt pool images. The images are acquired by a camera, mounted coaxially into the optical chain of the deposition head, which records images at 100 fps while the process is running. The proposed approach is explored experimentally by comparing the over-deposition measured on sample test geometries obtained with a traditional feed-forward approach with the over-deposition obtained through the developed closed-loop control laser deposition system.

Keywords

Metal additive manufacturing Vision systems Process monitoring Process control Predictive model 

Notes

Acknowledgments

The research in this paper has been partially funded by EU H2020-CS2-CFP02-2015-01, AMATHO Additive MAnufacturing of Tiltrotor HOusing. Contract 717194.

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.SUPSI, Institute of Systems and Technologies for Sustainable Production, Department of Innovative TechnologiesUniversity of Applied Sciences and Arts of Southern SwitzerlandMannoSwitzerland

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