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<p>Reliable dimensional inspection with handheld 3D scanners is frequently affected by unstable environmental conditions, reflective surfaces, and operator-dependent variability. This study introduces a practical, industry-oriented workflow designed to minimize noise during both acquisition and post-processing. The approach combines controlled lighting and temperature management, surface preparation using matte spray coatings, and optimized scanning trajectories to enhance data capture stability. These acquisition strategies are followed by a structured post-processing pipeline in Artec Studio 17, emphasizing targeted noise filtering while preserving small geometric features. Three machined components of differing complexity were evaluated, with dimensional accuracy assessed against their corresponding CAD models. The proposed workflow yielded average improvements of 1–2% in geometric fidelity and reduced variability across repeated scans. While the method relies on commercial software, it offers clear industrial value by improving inspection consistency, lowering rework rates, and supporting more efficient metrology practices. The findings provide actionable guidance for manufacturers seeking practical, workflow-based solutions for noise reduction in handheld 3D scanning environments.</p>

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An industry-oriented workflow for noise reduction in handheld 3D scanning: A case study in automated dimensional inspection

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月7日

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  • Scott Robinson,
  • Chengsi Lin,
  • Muhamad Arfauz A Rahman,
  • Paul G. Maropoulos,
  • Effendi Mohamad,
  • Teruaki Ito

摘要

Reliable dimensional inspection with handheld 3D scanners is frequently affected by unstable environmental conditions, reflective surfaces, and operator-dependent variability. This study introduces a practical, industry-oriented workflow designed to minimize noise during both acquisition and post-processing. The approach combines controlled lighting and temperature management, surface preparation using matte spray coatings, and optimized scanning trajectories to enhance data capture stability. These acquisition strategies are followed by a structured post-processing pipeline in Artec Studio 17, emphasizing targeted noise filtering while preserving small geometric features. Three machined components of differing complexity were evaluated, with dimensional accuracy assessed against their corresponding CAD models. The proposed workflow yielded average improvements of 1–2% in geometric fidelity and reduced variability across repeated scans. While the method relies on commercial software, it offers clear industrial value by improving inspection consistency, lowering rework rates, and supporting more efficient metrology practices. The findings provide actionable guidance for manufacturers seeking practical, workflow-based solutions for noise reduction in handheld 3D scanning environments.