Multi-head surface mounting placement optimisation based on adaptive multi-point crossover operator

• Published in: International journal for simulation and multidisciplinary design optimization Vol. 16; p. 8
• Main Authors: Song, Zhiqiang, Zhang, Chunfu
• Format: Journal Article
• Language: English
• Published: EDP Sciences 2025
• Subjects: genetic operator; pcb assembly; smt machine; surface mounting process optimisation
• ISSN: 1779-6288; 1779-6288
• DOI: 10.1051/smdo/2025007

Using different sequencing of component pick-and-place on a Surface Mount Technology (SMT) machine significantly impacts the distance required for head movement. The optimisation problem of surface mounting process optimisation in multi-head gantry-type SMT machine is generally considered to be an NP-hard problem. Therefore, study divides the surface mounting process optimisation into three sub-problems and propose a two-stage optimisation algorithm. In the first stage, a balanced distribution strategy (BDS) is introduced to address the component allocation problem, and a nearest neighbour algorithm (NNA) is proposed to solve the initial feeder allocation problem and component pick-and-place sequencing problems. Due to the large scale of the problem, finding the optimal solution within a reasonable time frame is challenging. Therefore, in the second stage, a novel genetic operator is proposed to further optimise the feeder sequence and the component pick-and-place sequence. Experimental results demonstrate that the proposed algorithm achieves high precision and speed. Specifically, compared with the minimum criterion genetic algorithm, the average distance is reduced by 4.15%, and compared with the multi-swarm discrete firefly algorithm, the average distance is reduced by 7.02%.