Development of an Assembly Sequence Planning and Simulation System Based on Assembly Accuracy

Assembly represents the culminating phase in the product production cycle, accounting for over 40% of production costs. Conventional assembly sequence planning methodologies predominantly prioritize geometric feasibility, tool change frequency, and directional change frequency as primary optimization objectives. Assembly accuracy is rarely systematically considered during the planning phase; instead, it is typically evaluated and optimized retrospectively after the production sequence has been established, making it difficult to effectively mitigate cumulative tolerances. During physical prototyping, failure to meet accuracy standards necessitates re-planning, which delays progress and increases costs. We propose an algorithm that integrates assembly accuracy prediction directly into the assembly sequence generation process. This enables sequence planning to be driven by constraints related to both assembly accuracy and efficiency. First, assembly precedence relationships are established based on the assembly information matrix to identify the base components. During the disassembly process, disassembly feasibility checks are incorporated to prevent the creation of isolated parts with no contact points, thereby enhancing the engineering soundness of the precedence modeling. Second, we propose an improved greedy topological sorting algorithm that incorporates assembly accuracy predictions as a key constraint in the objective function; by merging symmetrical parts in the prediction model to reduce the search space, the algorithm ultimately generates an assembly sequence that balances geometric feasibility, assembly efficiency, and assembly accuracy. Finally, we developed an integrated virtual assembly simulation system that combines assembly information extraction, sequence planning, and accuracy calculation, enabling the rapid generation and closed-loop verification of high-precision assembly sequences. Utilizing a simplified model as a case study, we generate comparison sequences with and without accuracy prediction and validate them through virtual assembly simulation. The experimental results show that, compared to traditional assembly sequences that do not account for precision, the proposed method improves the assembly precision pass rate by approximately 23% while maintaining assembly efficiency and significantly reduces the risk of rework and re-assembly caused by improper sequencing. Simulation software developed using this method can accurately plan assembly sequences for 25 parts in 223.58 s.