Nor Amalina Muhayudin
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Preferred name
Nor Amalina Muhayudin
Official Name
Nor Amalina, Muhayudin
Alternative Name
Muhayudin, Nor Amalina
Main Affiliation
Researcher ID
FQJ-2893-2022

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  • Publication
    Benchmarking artifact of selective laser sintering (SLS) components fabricated with flexible and rigid polymers
    (IOP Publishing Ltd, 2025-01)
    Hor Zian Shen
    ;
    Nor Amalina Muhayudin
    ;
    Tien-Dat Hoang
    ;
    Khairul Salleh Basaruddin
    ;
    Nur Liyana Tajul Lile
    ;
    Shah Fenner Khan Mohamad Khan
    This study aims to assess the performance of an Additive Manufacturing (AM) machine, specifically a Selective Laser Sintering (SLS) machine, through the design and evaluation of a benchmarking artifact. Drawing from insights gained in previous research, the artifact is meticulously crafted with two distinct materials to explore potential variations in geometric accuracy. The artifact comprises two types: one featuring straight geometries and another incorporating curved elements. The research methodology involves printing both artifact types at default machine settings, followed by precise measurements using a 3D scanner. The inclusion of straight and curved features facilitates a comprehensive examination of the machine’s ability to reproduce diverse geometries. The amalgamation of these features into a combined artifact provides a holistic assessment of the machine’s overall performance. To validate the benchmarking artifact, the final design is reproduced, and its output is compared not only with the original design but also with real-life parts. The results show that flexible polymers offer higher accuracy but lower resolution, while rigid polymers provide better resolution but with a greater number of defects. This comparative analysis serves to highlight the accuracy and reliability of the benchmarking artifact in reflecting the machine’s performance in practical scenarios. In conclusion, this study endeavours to advance the understanding of an SLS machine’s capabilities by leveraging a carefully designed benchmarking artifact.