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A Scan-Based Hierarchical Heuristic Optimization Algorithm for PCB Assembly Process
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DOI：10.1109/TII.2023.3312410.png)
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Surface mount technology is essential to the development of the electronic manufacturing industry. This article studies optimizing the surface mount process for the beam-head placement machine. A mixed-integer programming (MIP) model is proposed for this problem, which is decomposed into three interconnected hierarchical parts: feeder allocation; component assignment; and pick-and-place (PAP) sequence problems. This article proposes an efficient hierarchical framework with three elaborately designed heuristics to solve the above problem. The design of the scan-based algorithms optimizes the subobjectives of feeder allocation and component assignment. First, the allocation heuristic arranges the feeders into slots as a prerequisite for other problems. Then, the component assignment heuristic determines the component type for each head with a variety of criteria and long short-term objectives. Finally, the PAP sequence problem is solved using a modified beam search algorithm. The proposed algorithm offers advantages in terms of effectiveness, efficiency, and extension, which can satisfy various customization demands. Experiments are conducted on our self-designed placement machine using industrial and randomly generated data. Computational experiments show that the scan-based heuristic algorithm obtains near-optimal solutions with a gap of 9.93% averagely compared with the proposed MIP model and provides efficiency improvement over the mainstream studies.
Keyword:
Hierarchical decomposition
mixed-integer linear model
printed circuit board (PCB) assembly optimization
scan-based heuristic
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9.9
论文数:
8.6K
被引数:
6.0W
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Heuristic sequencing hopfield neural network for pick-and-place location routing in multi-functional placers.png)
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