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Related Experiment Video

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Multi-objective optimization for minimize cutting force and power consumption in corn stalk chopping processes.

Kurre Prasanth Kumar Reddy1, S Ramesh Kumar1, Boggarapu Nageswara Rao1

  • 1Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Deemed to be University, Green Fields, Vaddeswaram, Guntur, 522302, India.

Heliyon
|August 21, 2024
PubMed
Summary
This summary is machine-generated.

Optimizing corn stalk chopping reduces cutting force and power consumption. The study identified optimal parameters for efficient biomass processing, minimizing energy use in agricultural machinery.

Keywords:
Approach angleChauvenet's criterionCorn stalksFeeding angleVelocity

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Area of Science:

  • Agricultural Engineering
  • Biomass Processing
  • Sustainable Agriculture

Background:

  • Corn stalks are valuable biomass and forage resources.
  • Reducing cutting force is key to improving energy efficiency in biomass processing.
  • High cutting velocity can increase power consumption without proportional reduction in shear forces.

Purpose of the Study:

  • To minimize both cutting force and power consumption during corn stalk chopping.
  • To optimize the parameters of the corn stalk cutting process for enhanced energy efficiency.

Main Methods:

  • A modified Taguchi method was used for multi-objective optimization.
  • Chauvenet's criterion was applied to validate statistical data scatter.
  • Analysis of Variance (ANOVA) was employed to identify optimal process parameters.

Main Results:

  • Optimal parameters identified: velocity of 4.4 m/s, approach angle of 30°, and feeding angle of 50°.
  • Empirical relationships predict cutting force between 180.55 N and 393.37 N.
  • Predicted cutting power ranges from 16.81 W to 44.05 W.
  • Optimal parameter set yielded 26.32 W power consumption and 242.60 N cutting force.

Conclusions:

  • The identified optimal parameters significantly reduce cutting force and power consumption for corn stalk chopping.
  • Findings provide valuable insights for operating chopping machines efficiently.
  • Variations in corn stalk thickness may contribute to data scatter in repeated tests.