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Determining Surface Topography of a Dressed Grinding Wheel Using Bio-Inspired DNA-Based Computing.

Akihiko Kubo1, Roberto Teti2, Amm Sharif Ullah1

  • 1Division of Mechanical and Electrical Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami 090-8507, Japan.

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Summary

DNA-based computing (DBC) offers a faster, computationally efficient method for analyzing grinding wheel topography. This bio-inspired approach accurately identifies active abrasive grains, optimizing dressing operations for improved surface finish in manufacturing.

Keywords:
DNA-based computingbio-inspired manufacturingdressinggrindingimage processingsurface topography

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Area of Science:

  • Manufacturing Engineering
  • Computational Biology
  • Materials Science

Background:

  • Grinding is crucial for surface finish on hard/brittle materials.
  • Effective grinding relies on optimal distribution of active abrasive grains on the wheel surface.
  • Dressing operations maintain grain distribution, with effectiveness assessed via surface topography analysis.

Purpose of the Study:

  • To introduce DNA-based computing (DBC) as a bio-inspired alternative for analyzing grinding wheel topography.
  • To demonstrate DBC's capability in distinguishing grain-bearing regions from non-grain regions.
  • To reduce computational load and time compared to traditional image processing methods.

Main Methods:

  • Application of DNA-based computing (DBC), a bio-inspiration-based method.
  • Analysis of grinding wheel surface topography.
  • Comparison of DBC results with traditional image processing techniques.

Main Results:

  • DBC effectively eliminates non-grain regions while preserving grain regions.
  • Significant reduction in computational effort and time compared to conventional image processing.
  • Reduced potential grain regions from ~7000 to ~300 on a tested surface area.

Conclusions:

  • DBC provides a computationally efficient and effective method for grinding wheel topography analysis.
  • This approach can lead to optimized dressing and grinding operations.
  • The study supports the