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Soft Computing Techniques for Laser-Induced Surface Wettability Control.

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Summary

Fuzzy logic optimizes laser surface texturing for wettability control by managing process uncertainties. This approach successfully adjusted contact angles on AISI 304 steel, demonstrating improved control over surface properties.

Keywords:
fuzzy logicgenetic algorithmslaser texturingsoft computingwettability.

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Area of Science:

  • Materials Science
  • Manufacturing Engineering
  • Control Systems

Background:

  • Manufacturing decisions involve uncertainties, impacting productivity and quality.
  • Fuzzy logic effectively incorporates imperfect information for optimization.
  • Laser surface texturing for wettability control is complex due to numerous interacting parameters.

Purpose of the Study:

  • To develop a fuzzy-based decision approach for laser surface texturing.
  • To account for random and systematic errors in the process.
  • To optimize wettability control by managing uncertainties.

Main Methods:

  • Laser surface texturing using a nanosecond-pulsed laser on AISI 304 samples.
  • Varied laser scanning speed, hatch distance, number of repetitions, and scanning pattern.
  • Implemented a fuzzy-based decision model to propagate uncertainties.

Main Results:

  • Achieved significant changes in contact angle, ranging from 24° to 121°.
  • Demonstrated the capability of fuzzy logic to handle process variability and modeling assumptions.
  • Fuzzy maps visualized inherent uncertainties in laser texturing and the model.

Conclusions:

  • The fuzzy-based approach effectively manages uncertainties in laser surface texturing for wettability control.
  • This method allows for optimization of productivity and final surface quality.
  • The study highlights the importance of considering process and model uncertainties for reliable control.