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Optimization of an autonomous robotic drilling system for the machining of aluminum aerospace alloys

Benjamin Pereira, Christian Griffiths, Benjamin Birch, Andrew Rees

The International Journal of Advanced Manufacturing Technology, Volume: 119, Issue: 3-4, Pages: 2429 - 2444

Swansea University Authors: Christian Griffiths, Andrew Rees

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Abstract

This paper aims to identify the capability of a highly fexible industrial robot modifed with a high-speed machine spindle for drilling of aluminum 6061-T6. With a focus on drilling feed rate, spindle speed, and pecking cycle, the hole surface roughness and exit burr heights were investigated using t...

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Published in: The International Journal of Advanced Manufacturing Technology
ISSN: 0268-3768 1433-3015
Published: Springer Science and Business Media LLC 2022
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa59023
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Abstract: This paper aims to identify the capability of a highly fexible industrial robot modifed with a high-speed machine spindle for drilling of aluminum 6061-T6. With a focus on drilling feed rate, spindle speed, and pecking cycle, the hole surface roughness and exit burr heights were investigated using the Taguchi design methodology. A state of the art condition monitoring system was used to identify the vibrations experienced during drilling operation and to establish which robot pose had increased stifness, and thus the optimum workspace for drilling. When benchmarked against a CNC machine the results show that the CNC was capable of producing the best surface fnish and the lowest burr heights. However, the robot system matched and outperformed the CNC in several experiments and there is much scope for further optimization of the process. By identifying the optimum pose for drilling together with the idealized settings, the proposed drilling system is shown to be far more fexible than a CNC milling machine and when considering the optimized drilling of aerospace aluminum this robotic solution has the potential to drastically improve productivity
Keywords: Automation; Robotics; Drilling; Machine spindle; Aerospace alloys
College: Faculty of Science and Engineering
Funders: Support of the Future Manufacturing Research Institute, College of Engineering, Swansea University and Advanced Sustainable Manufacturing Technologies (ASTUTE 2022) project, which is partly funded from the EU’s European Regional Development Fund through the Welsh European Funding Office
Issue: 3-4
Start Page: 2429
End Page: 2444