Increasing performance demands in aerospace, energy, and advanced manufacturing systems require mechanical designs capable of operating under strongly coupled thermal, mechanical, fluidic, and electromagnetic conditions. Conventional single-physics optimization approaches are insufficient to capture nonlinear interactions that govern durability, efficiency, and structural stability in next-generation engineering systems. This study aims to develop an integrated multiphysics optimization framework that bridges material-level constitutive behavior with mechanism-level system performance. A computational research design was employed, combining physics-based multiphysics modeling, finite element analysis, computational fluid dynamics, and multi-objective optimization algorithms within a unified architecture. Temperature-dependent and nonlinear material properties were dynamically updated during iterative optimization cycles. Physics-informed surrogate modeling was incorporated to accelerate convergence while maintaining predictive reliability. Three representative case systems were evaluated to validate the proposed framework. Results indicate significant improvements in structural and energetic performance, including reductions in peak stress and thermal gradients, enhanced fatigue life, improved vibration stability, and increased energy efficiency. Statistical analysis confirmed the robustness and practical significance of these improvements. The study concludes that mechanism-centered multiphysics optimization represents a critical advancement beyond conventional sequential design strategies, offering a scalable and reliable pathway for developing resilient, high-performance mechanical systems.