Lightweight design of excavator working device based on automatically generated surrogate model

Area of Science:

• Mechanical Engineering
• Structural Optimization
• Computational Mechanics

Background:

• Traditional excavator working device design methods result in conservative configurations, often leading to excessive weight.
• Optimizing excavator boom design is crucial for enhancing operational efficiency and reducing fuel consumption.
• Lightweighting structural components without compromising performance is a key challenge in heavy machinery design.

Purpose of the Study:

• To develop and validate a lightweight structure design method for excavator working devices.
• To identify significant boom design parameters influencing mass, deformation, and stress.
• To achieve a minimized mass for the excavator boom while satisfying stress and deformation constraints.

Main Methods:

• Construction and experimental validation of a finite element model for the excavator working device.
• Enhancement of the entropy-weighted TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method using the Gini coefficient for parameter significance analysis.
• Development of a surrogate model using 500 sample points and optimization via a genetic algorithm.

Main Results:

• Identification of critical boom design parameters through the enhanced entropy-weighted TOPSIS method.
• Successful construction of a surrogate model for the working device.
• A lightweight design for the hydraulic excavator boom was achieved, reducing its weight by 9.30%.

Conclusions:

• The proposed lightweight design method effectively reduces excavator boom mass.
• Finite element simulations confirm that the optimized design meets stress and deformation requirements.
• This approach offers a viable strategy for optimizing heavy machinery components for weight reduction and performance.