Academic Journal of Engineering and Technology Science, 2022, 5(1); doi: 10.25236/AJETS.2022.050102.
Zaozhuang University, Zaozhuang, Shandong, 266700, China
Assembly, the key to the entire product production, has a direct impact on product quality. The parts of various products are optimized and matched according to the prescribed rules by using computer technology, and the best matching scheme is finally obtained. This method can effectively ensure the assembly accuracy of the parts and reduce the residual rate of the parts. This paper proposes an optimized grouping and matching method based on genetic algorithm for the selection of complex mechanical products, and redefines the structure of dyeing, and provides technical support for the intelligent development of mechanical manufacturing.
Selective Assembly, Surplus Parts, Genetic Algorithm
Xu Wei. Research on the Selection and Matching of Complex Mechanical Products Based on Genetic Algorithms. Academic Journal of Engineering and Technology Science (2022) Vol. 5, Issue 1: 4-9. https://doi.org/10.25236/AJETS.2022.050102.
 Nagarajan L, Mahalingam SK, Kandasamy J , et al. A novel approach in selective assembly with an arbitrary distribution to minimize clearance variation using evolutionary algorithms: a comparative study[J]. Journal of Intelligent Manufacturing, 2021(11).
 Arram A , Ayob M . A novel Multi-parent order crossover in Genetic Algorithm for combinatorial optimization problems[J]. Computers & Industrial Engineering, 2019, 133(JUL.):267-274.
 H Zhao, Zhan Z H , Chen W N , et al. An Improved Selection Operator for Multi-objective Optimization[J]. 2019.
 Gao S, Zhang R. Rapid calibration method of MEMS accelerometer based on adaptive GA[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019.
 Luo F, Fanglin L, Hou Z. An Improved Genetic Algorithm Based on Elite Retention Strategy and Explosion Operators[J]. Journal of Xihua University(Natural Science Edition), 2018.