This study presents computational and biomechanical models to analyze mechanical power consumption in train assemblers' work at railway stations. The research integrates physical and mathematical modeling to quantify energy expenditure based on movement mechanics, joint torques, and muscle forces. A multi-link biomechanical system is employed to evaluate efficiency during tasks such as walking, climbing, and handling brake shoes. Key findings reveal that energy expenditure varies significantly with task complexity, with "external work" (e.g., lifting) requiring up to 200 W and "internal work" (e.g., muscle coordination) consuming 400 W, totaling 600 W of mechanical power. The models demonstrate that optimizing movement techniques and ergonomic interventions can reduce energy waste by up to 30%. These results provide a data-driven framework for assessing professional suitability, improving occupational safety, and enhancing labor efficiency in railway operations. The study advances digital modeling in biomechanics and lays the groundwork for future research on real-time monitoring and AI-driven predictive modeling.