A MCVRP-based model for PCB assembly optimisation on the beam-type placement machine

Shujuan Guo, Fei Geng, Katsuhiko Takahashi, Xiaohan Wang and Zhihong Jin

International Journal of Production Research, 2019, vol. 57, issue 18, 5874-5891

Abstract: The beam-type placement machine is capable of picking up multiple components simultaneously from the feeders in printed circuit board (PCB) assembly. Simultaneous pickup occurs only if the heads in the beam are aligned with the feeders and the nozzle-types on these heads match with the component-types on the feeders. In order to minimise the assembly cycle time, the optimisation problem is decomposed into two sub-problems, the pickup combination and sequencing problem, and the placement cluster and sequencing problem. These two sub-problems are simultaneously solved by the proposed hybrid genetic algorithm (HGA). The pickup combination and sequencing problem is similar to the popular multi-compartment vehicle routing problem (MCVRP); a genetic algorithm (GA) for the MCVRP is therefore modified and applied to solving the pickup combination and sequencing problem. A greedy heuristic algorithm is used to solve the placement cluster and sequencing problem. The numerical experiments reveal that the HGA outperforms the algorithms proposed by previous papers.

Date: 2019
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DOI: 10.1080/00207543.2018.1555380

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