The use of generative design technologies in optimizing the construction of construction machinery: impact on productivity and efficiency
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Abstract
Modern construction engineering is faced with the need to optimize structures to increase productivity while reducing material consumption and energy consumption. Generative design is an innovative approach based on algorithmic design using artificial intelligence, which allows you to create optimized designs that are unattainable with traditional design. This study is aimed at a comprehensive assessment of the impact of generative design methods on the operational and economic performance of construction machinery. The paper uses methods of finite element analysis, topological optimization and multi-criteria comparative analysis. The empirical base includes the results of computer modeling and field tests of modified structural elements of the EO-5126 excavator and the KS-65740 truck crane. The study demonstrates that the use of generative design makes it possible to reduce the mass of key structural elements by 18-27% while maintaining strength characteristics, increase structural rigidity by 12.4%, reduce fuel consumption by 8.2% and reduce production costs by 15.3%. The life cycle analysis shows an 11.7% reduction in the carbon footprint when operating optimized machines. The results indicate a significant potential for integrating generative design technologies into the design processes of construction machinery, providing a synergistic effect: increasing technical characteristics while reducing resource consumption and environmental burden.
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References
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