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Optimal Design for Compliant Mechanism Flexure Hinges: Bridge-Type.

Chia-Nan Wang1, Fu-Chiang Yang1, Van Thanh Tien Nguyen1,2

  • 1Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan.

Micromachines
|November 27, 2021
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Summary

Researchers optimized compliant mechanisms using grey relational analysis and finite element analysis. This design achieved a 65.36x displacement amplification ratio with minimal stress and friction, validated experimentally.

Keywords:
artificial neural networkcompliant mechanismgrey-based Taguchi methodoptimization design

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Area of Science:

  • Mechanical Engineering
  • Materials Science

Background:

  • Compliant mechanisms offer advantages like larger workspaces and simpler structures.
  • Traditional designs often face limitations in workspace and can experience friction and bending.

Purpose of the Study:

  • To design optimal bridge-type compliant mechanism flexure hinges.
  • Achieve high displacement magnification, low stress, and eliminate friction and bending.

Main Methods:

  • Utilized Grey Relational Analysis (GRA) based on the Taguchi Method (TM).
  • Employed Finite Element Analysis (FEA) for design optimization.
  • Estimated Grey Relational Grade (GRG) using an Artificial Neural Network (ANN).

Main Results:

  • Optimal dimensions were determined for the flexure hinges.
  • Finite Element Analysis confirmed significant impact of design dimensions on stress and displacement.
  • Experimental validation showed results within 6% deviation of predicted values.

Conclusions:

  • The optimized compliant mechanism achieved a displacement amplification ratio of 65.36 times.
  • The design successfully minimized stress and eliminated friction and bending.
  • The integrated approach of GRA, TM, and FEA proved effective for optimizing compliant mechanisms.