Optimization of the Structural Design of a Vertical Lathe Table in the Context of Minimizing Thermal Deformations

Modern machining industries require high precision and efficiency in machine tools, where thermal deformations significantly impact accuracy. This study focuses on optimizing the structural parameters of a vertical turning center to minimize thermal displacements affecting machining precision. The optimization process is divided into parametric and topological methodologies. The parametric approach targets three primary objectives: minimizing mass (q₁), maximizing static stiffness (q₂), and reducing thermal displacement (q₃). Multi-criteria optimization techniques, including Pareto-based and scalarization methods, are applied to balance these conflicting factors. Finite Element Analysis (FEA) models assist in evaluating machine stiffness and displacement, with constraints imposed on structural mass and stiffness to maintain performance. Parametric optimization, using iterative computational algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), refines rib and wall thicknesses of the lathe table to achieve displacement reductions. The optimization process successfully lowers displacement at critical measurement points while maintaining structural integrity. Hybrid PSO (hPSO) outperforms other algorithms in achieving optimal parameter sets with minimal computational effort. Topological optimization, based on the Solid Isotropic Microstructure with Penalization (SIMP) method, further enhances structural efficiency by refining material distribution. The iterative process identifies optimal energy flow paths while ensuring compliance with mechanical constraints. A hybrid approach integrating parametric adjustments with topological refinement leads to superior performance, achieving a 43% reduction in displacement at key measurement points compared to the initial design. The final optimized design reduces mass by 1 ton compared to the original model and 2.5 tons compared to the best rib–wall optimization results. The study’s findings establish a foundation for implementing active deformation compensation systems in machine tools, enhancing machining precision. The integration of parametric and topological optimization presents a robust framework for designing machine tool structures with improved thermal stability and structural efficiency.