This study introduces a novel application of Particle Swarm Optimization (PSO) for tool path planning of louvre geometries to be utilized in heat transfer procedure. Particular emphasis of this study is focused on achieving smooth, non-intersecting trajectories and minimized time machining. Unlike conventional approaches, the proposed method ensures collision-free tool movements while simultaneously minimizing redundant motions and machining-induced defects. This contribution is important for industrial machining operation as it is not only capable in improving operational safety but also significantly reductions in machining time, energy consumption, and surface defects. Experimental evaluations reveal that PSO delivers rapid time machining of 0.60 minutes or 36 seconds and stable convergence in its optimization process. Even though, the average objective function drops sharply within the first 50 iterations and it finally stabilizes near iteration 80. Interestingly, the minimum objective value remains constant from the outset, indicating that an optimal solution has been reached the early stage. Accordingly, the optimization of PSO for louvre geometry in heat transfer performance reflects an identified high-quality solution. The future extensions can emphasize on including adaptive mutation, diverse initialization schemes, reduced selection pressure, and restart mechanisms. Overall, this research not only validates the potential of PSO for complex geometries such as louvre machining tasks but also identifies new directions for a more reliable optimization frameworks in advanced manufacturing.