Efficient method of assembly sequence planning based on GAAA and optimizing by assembly path feedback for complex product

Abstract

In the process of complex product assembly, assembly resources (fixtures, tools, operations, and so on) must enter assembly environment with parts together to rapidly finish product assembly. Assembly planning must take assembly resources into account fully. But, designer cannot plan every assembly procedure because of the lack of assembly resources during assembly design. Then, it will cause assembly failures and redesign for assembly easily. This paper investigates an efficient method of assembly sequence planning based on genetic algorithm and ants algorithm (GAAA) and optimizing by assembly path feedback to assembly process planning including assembly resources for complex products. Firstly, a new GAAA is investigated to rapidly plan assembly sequence in order to solve the nondeterministic polynomial-bounded problem in high searching and solving efficiency. Secondly, on the basis of the assembly sequence, a B-Rep filling algorithm which can form a swept volume between the part and its kinetic orientation is developed to plan assembly path interactively. Thirdly, the performance of the assembly path according to the assembly sequence is analyzed and sent back to avoid the most of assembly collisions and interventions during product assembly design. Lastly, we develop a simulating system to simulate assembly sequence and path based on component application architecture for CATIA V5. The simulating result proved that the proposed method of assembly sequence planning based on GAAA and optimizing by assembly path feedback for complex products is efficient. Assembly optimal design including assembly resources can work well.