Application of Artificial Intelligence in the Development of an Industrial Design Concept for Next-Generation Agricultural Tractors

The integration of Artificial Intelligence (AI) into industrial design is fundamentally transforming the development of agricultural machinery. This paper presents an expanded AI-driven framework for the industrial design of next-generation agricultural tractors. The proposed methodology integrates generative design algorithms, computational fluid dynamics (CFD), ergonomic simulation, finite element analysis (FEA), digital twin modeling, and AI-based material optimization within a unified design ecosystem. The study identifies limitations in traditional tractor development methods, which rely on manual prototyping, sequential testing, and limited predictive modeling. The AI-integrated framework enables data-driven structural optimization, aerodynamic refinement, ergonomic customization, and cost-efficient virtual validation before physical manufacturing. Quantitative results demonstrate an 8–12% reduction in fuel consumption through weight minimization and airflow optimization, a 25% reduction in physical prototyping costs, and measurable improvements in operator comfort and visibility. The research contributes a scalable AI-based industrial design model tailored specifically to agricultural engineering applications.