# Research and experimental verification of lightweight loader rims

## TL;DR

This paper explores lightweight and strong loader rims to improve machine performance and reduce environmental impact.

## Contribution

A novel multiobjective optimization approach using genetic algorithms and response surface methods for rim design.

## Key findings

- Optimized rim designs balance weight reduction and structural performance.
- Field tests confirmed the reliability of simulation results.
- Production costs were considered alongside performance metrics in final design selection.

## Abstract

The safety performance and structural stiffness of a rim, which is the main load-bearing structure of the loader during operation, influence the overall performance, stability, and braking capabilities of the machine. In the industry, researchers are currently pursuing lightweight and high-strength rims as a primary objective. A low weight not only enhances machinery fuel efficiency but also aligns with societal demands for sustainable development, energy conservation, and emission reduction. In this article, multiobjective optimization analysis on rims composed of three different materials is performed, and the relationships between various optimization parameters and target parameters are established using the results of response surface construction. Multiobjective genetic algorithms are utilized to derive various optimization plans, which are subsequently evaluated through static analysis, fatigue analysis, and weight loss analysis. The final optimization plan is determined based on the calculation results while considering production costs. Field tests are conducted on the optimized rims under various working conditions to verify the test results, evaluate the reliability of the finite element analysis results, and confirm the safety of the optimized rim.