Abstract: An assembly sequence planning (ASP) method that combined the advantages of ant colony system (ACS) and max-min ant system (MMAS) is proposed. Several characteristics that adopted in the literatures of the ASP based on ant colony optimization (ACO) in the last decade are reviewed and compared, such as the optimization criterions, the assembly information models, the numbers of components in cases study. To identify good sequences more obviously, five optimization criterions are automatically quantified, including directionality, parallelism, continuity, stability and auxiliary stroke, and integrated into the multi-objective heuristic and fitness functions of ACO. To improve the search capability for the global best sequence based on geometric assembly feasibility, several measures are presented from the aspects of determining ant number, defining max-min pheromone, and the mechanisms of performance appraisal for initial components allocation and parallel components group enforcement. Then the ASP algorithm based on max-min ant colony system (MMACS) is proposed. An assembly planning system “AutoAssem” is developed based on Siemens NX platform, and the actual effectiveness of each optimization measure is testified through case study of a valve. Compared with priority rules screening, genetic algorithm and particle swarm optimization, the superiority of the algorithm in executive efficiency and sequence performance are analyzed.

Key words: Ant colony optimization algorithm, Assembly sequence planning, Extended interference matrix, Max-min ant system