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Improving surface quality in selective laser melting based tool making

Author

Listed:
  • Filippo Simoni

    (OWL University of Applied Sciences and Arts)

  • Andrea Huxol

    (OWL University of Applied Sciences and Arts)

  • Franz-Josef Villmer

    (OWL University of Applied Sciences and Arts)

Abstract

In the last years, Additive Manufacturing, thanks to its capability of continuous improvements in performance and cost-efficiency, was able to partly replace and redefine well-established manufacturing processes. This research is based on the idea to achieve great cost and operational benefits especially in the field of tool making for injection molding by combining traditional and additive manufacturing in one process chain. Special attention is given to the surface quality in terms of surface roughness and its optimization directly in the Selective Laser Melting process. This article presents the possibility for a remelting process of the SLM parts as a way to optimize the surfaces of the produced parts. The influence of laser remelting on the surface roughness of the parts is analyzed while varying machine parameters like laser power and scan settings. Laser remelting with optimized parameter settings considerably improves the surface quality of SLM parts and is a great starting point for further post-processing techniques, which require a low initial value of surface roughness.

Suggested Citation

  • Filippo Simoni & Andrea Huxol & Franz-Josef Villmer, 2021. "Improving surface quality in selective laser melting based tool making," Journal of Intelligent Manufacturing, Springer, vol. 32(7), pages 1927-1938, October.
    • Handle: RePEc:spr:joinma:v:32:y:2021:i:7:d:10.1007_s10845-021-01744-9
    DOI: 10.1007/s10845-021-01744-9
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    References listed on IDEAS

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    1. William Mycroft & Mordechai Katzman & Samuel Tammas-Williams & Everth Hernandez-Nava & George Panoutsos & Iain Todd & Visakan Kadirkamanathan, 2020. "A data-driven approach for predicting printability in metal additive manufacturing processes," Journal of Intelligent Manufacturing, Springer, vol. 31(7), pages 1769-1781, October.
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    Cited by:

    1. Christian Spreafico & Davide Russo & Riccardo Degl’Innocenti, 2022. "Laser pyrolysis in papers and patents," Journal of Intelligent Manufacturing, Springer, vol. 33(2), pages 353-385, February.
    2. Dongxiang Hou & Xiaodong Wang & Qing Song & Xuesong Mei & Haicheng Wang, 2024. "A quality improvement method for complex component fine manufacturing based on terminal laser beam deflection compensation," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 331-341, January.

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