| Issue |
Manufacturing Rev.
Volume 13, 2026
|
|
|---|---|---|
| Article Number | 11 | |
| Number of page(s) | 10 | |
| DOI | https://doi.org/10.1051/mfreview/2026005 | |
| Published online | 05 June 2026 | |
Original Article
Hybrid path planning method for PCB drilling based on feature-aware and zone-optimization strategy
1
Anyang Institute of Technology, Anyang 455000, PR China
2
Henan Xiangyu Medical Equipment Co., Ltd. Anyang 455000, PR China
* e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
7
November
2025
Accepted:
12
May
2026
Abstract
To improve machining efficiency, this paper investigates the path optimization problem in numerically controlled drilling of printed circuit boards. The traditional Traveling Salesman Problem model exhibits significant limitations when applied to circuit boards characterized by high density and repetitive hole patterns. By analyzing spatial distribution features such as cluster distribution and module reuse of the holes, a hybrid path optimization algorithm is proposed. This method identifies holes with regular distributions and clusters them as macro operation units. A hierarchical optimization strategy is then adopted, performing inter-zone optimization first followed by intra-zone optimization. Decomposing the large-scale Traveling Salesman Problem into multiple smaller sub-problems significantly reduces computational complexity. By integrating the optimization of cluster entry/exit points with the 2-opt algorithm, a holistic optimization of both global and local paths is achieved. Simulation experiments demonstrate that the proposed method significantly reduces both the total drilling path length and computation time compared to conventional optimization methods.
Key words: PCB drilling / traveling salesman problem / hierarchical optimization strategy / holistic path optimization
© W. Yang et al., Published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.
