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<p>In additive manufacturing (AM), the removal of support structures is a critical post-processing step that significantly impacts the quality and functionality of the final product. This study investigates high-efficiency techniques for removing support structures in fused deposition modeling printed parts, focusing on polyvinyl butyral as a support material. Four distinct support geometries were evaluated using three removal methods: manual removal, ethanol-based solvent treatment, and a hybrid approach combining mechanical and chemical techniques. The hybrid method demonstrated the highest efficiency, reducing removal time by up to 70.3% and increasing the removal rate by 4.07 times compared to manual removal. These findings highlight the potential of hybrid methods for optimizing support material removal in AM, particularly for complex geometries. The study provides valuable insights for improving post-processing efficiency and product quality in AM applications.</p>

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Innovative approaches and applications of high-efficiency techniques for support structure removal in additive manufacturing

  • 期刊论文

  • 发表日期：

    2025年4月1日

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  • Chil-Chyuan Kuo,
  • Zi-En Jian,
  • Song-Hua Huang,
  • Armaan Farooqui

摘要

In additive manufacturing (AM), the removal of support structures is a critical post-processing step that significantly impacts the quality and functionality of the final product. This study investigates high-efficiency techniques for removing support structures in fused deposition modeling printed parts, focusing on polyvinyl butyral as a support material. Four distinct support geometries were evaluated using three removal methods: manual removal, ethanol-based solvent treatment, and a hybrid approach combining mechanical and chemical techniques. The hybrid method demonstrated the highest efficiency, reducing removal time by up to 70.3% and increasing the removal rate by 4.07 times compared to manual removal. These findings highlight the potential of hybrid methods for optimizing support material removal in AM, particularly for complex geometries. The study provides valuable insights for improving post-processing efficiency and product quality in AM applications.