Efficient packing of irregular mechanical parts in limited container space is essential for reducing transportation and storage costs in automated manufacturing. This study focuses on eccentric-shaped parts characterized by geometric asymmetry, multiple orientations, and local irregularities, and proposes a two-stage three-dimensional packing strategy. In the first stage, an optimal single-layer layout is generated using a heuristic algorithm that combines grid scanning with a gravity-drop principle and tabu search to optimize part positions and orientations. In the second stage, the optimized layer template is vertically replicated with buffer layers to enhance stacking stability, ensuring feasible and non-overlapping arrangements. Comparative experiments with Best Fit, BLF, LHL, and Random methods show that the proposed approach increases average space utilization by 8.3%, 8.8%, 8.1%, and 15.5%, respectively, while maintaining high stability and reasonable computation time. The results demonstrate that this method achieves dense and stable packing, offering an effective solution for intelligent packing and automated production of irregular parts.