Online Control Threshold Optimization for Complex Mechanical Products Assembly Process Based on Hybrid Genetic Particle Swarm Optimization

doi:10.3901/JME.2016.01.130

Abstract

Abstract: To improve assembly precision and service safety performance for complex mechanical products, an online control threshold optimization approach based on hybrid genetic particle swarm optimization is put forward. First, the characteristics of complex mechanical product assembly and service are analyzed, and the key quality control points’ multiple load influence factor is defined. Assembly quality loss cost and assembly time cost are considered, the assembly cost-control threshold function based on multiple load influence factor is established to describe the relationship between the assembly tolerance and the cost. In the case of ensuring the accuracy of the assembly, the online control threshold optimization model is established. And the process of hybrid genetic particle swarm optimization model for gaining the minimum assembly cost is given. Finally, an example of online tolerance optimization model in the assembly process of the engine cylinder head is given. The results show that the method can significantly improve the quality of assembly and service safety performance by comparing analysis the present method and the previous’, and a practical method for complex mechanical product assembly quality online control is provided.

Key words: assembly cost-control threshold function, assembly quality, hybrid particle swarm optimization, multiple load influence factor, online control threshold optimization

CLC Number:

TH161
TP391

WANG Xiaoqiao, LIU Mingzhou, GE Maogen, MA Jing, LIU Conghu. Online Control Threshold Optimization for Complex Mechanical Products Assembly Process Based on Hybrid Genetic Particle Swarm Optimization[J]. Journal of Mechanical Engineering, 2016, 52(1): 130-138.

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