Assembly sequence planning based on a hybrid particle swarm optimisation and genetic algorithm

Abstract

Assembly sequence planning (ASP) plays a key role in the whole life circle of a product. ASP has a great impact on variation propagation, production quality and efficiency of the assembly process. This paper tries to provide the way to generate and optimise assembly sequence for compliant assemblies based on graph theory. Firstly, a liaison graph and adjacency matrix are used to describe the geometry of the compliant assemblies. Secondly, an assembly sequence is represented by a character string, whose length is the number of all parts. The conceptual tolerance analysis is used to evaluate feasible sequences. Finally, the hybrid particle swarm optimisation and genetic algorithm is presented to generate assembly sequences. The hybrid particle swarm optimisation and genetic algorithm is more effective than the particle swarm optimisation, the genetic algorithm, the matrix operation and the enumeration method for assembly sequence planning of compliant assemblies.

Keywords:

• assembly sequence planning
• particle swarm optimisation
• genetic algorithm
• graph theory

Acknowledgements

This work was supported by the Shanghai Natural Science Foundation (No. 11ZR1414700) and National Natural Science Foundation of China (No. 51105241).