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A Scan-Based Hierarchical Heuristic Optimization Algorithm for PCB Assembly Process

delete2024-03-01
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PRE
AI
G
Guangyu Lu
X
Xinghu Yu
H
Hao Sun
Z
Zhengkai Li
J
Jianbin Qiu
高会军 (Huijun Gao) *
DOI:10.1109/TII.2023.3312410delete
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Abstract

Abstract

En 中文
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.
Keywords:
Hierarchical decomposition
mixed-integer linear model
printed circuit board (PCB) assembly optimization
scan-based heuristic

Journal

IEEE Transactions on Industrial Informatics cover
IEEE Transactions on Industrial Informatics
IF:
9.9
Papers:
8.3K
Citations:
6.0W

Organization

H
harbin institute of technology
Scholars:
8.0W
Papers: 6.6W
Citations: 66
P
Peng Cheng Laboratory
Scholars:
1.7K
Papers: 1.8K
Citations: 2.0K
S
shenzhen university
Scholars:
4.5W
Papers: 3.4W
Citations: 72
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