This thesis represents an initial and foundational step within a larger research project focused on predicting and controlling key outcomes in complex thermomechanical processes, such as final geometry, microstructure, and residual stresses, based on known input parameters. We adopted Isogeometric Analysis (IGA) due to its precise and efficient geometric modeling capabilities and its superior approximation properties compared to traditional strategies, like the Finite Element Method (FEM) [1]. One of the main challenges of IGA is its high computational demand, especially when using high-order and high-continuous spline functions [2]. To address this difficulty, we implemented innovative techniques, including Weighted Quadrature [3], Matrix-Free [4], and Fast Diagonalization [5]. Although these approaches are typically applied independently, this work integrated them into a robust and versatile strategy that significantly reduces CPU time and memory consumption while maintaining the accuracy of the results. We enhanced the preconditioner based on the classical Fast Diagonalization algorithm by incorporating geometric and material information, along with more user-friendly procedures compared to the existing approach, while keeping a similar runtime. Additionally, we addressed challenges related to material nonlinearity in elastoplasticity and heat transfer problems. For the latter, we devised a space-time scheme that, when combined with these methodologies, enables IGA to outperform traditional FEM-based techniques by efficiently solving the fully coupled (d + 1)-dimensional system directly, instead of incrementally solving d-dimensional problems. Our findings establish a foundation for more realistic industrial applications and open new research directions, such as adaptive refinement and discontinuous methods, aimed at overcoming current limitations in elastoplasticity and mitigating numerical instabilities caused by moving heat sources. This work advances the current state of IGA and paves the way for future innovations in computational mechanics, enabling faster, more accurate, and more reliable simulations.