In order to explore the full potential of generative design we have conducted a study on a 245G LC john deere excavator arm without any restriction in terms of preserved geometry, desired weight, standardization, and structural limitations.
Our aim was to lightweight the part while maintaining the same structural integrity in terms of resistance, lifting power, working feasibility, and factor of safety, compared to the original design.
The focus was on reducing CO2 emissions and environmental impact calculated over the excavator's lifetime by adopting our generative design solution.
In this case study our primary focus was to emphasize the advantages offered by generative design in reducing fuel consumption and the negative environmental impact of CO2 emissions.
Rather than following a heavy-engineered approach, we allowed the generative design AI algorithm full freedom to explore design possibilities ā a standardized procedure would have increased time and resources considerably.
We avoided imposing structural constraints so as to preserve the original geometry, while still maintaining feasible structural integrity and a sufficient factor of safety.
The final topology optimised design shows a 13.3% reduction in mass compared to the original excavator arm: this product is about 90kg lighter, fuel consumption is reduced by 2520l/lt, and CO2 emissions are reduced by 40594 kg.
The generative design shows a 56.2% reduction in mass compared to the original excavator arm: this product is about 380kg lighter, fuel consumption is reduced by 4759l/lt, and CO2 emissions are reduced by 74889 kg.