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案件記録

Time-Optimal Placement Path Optimization Method for Surface Mounters

発明審査中
8閲覧数
10請求項 · 1 独立
§ Ⅰ

案件概要

発明者

Huijun GAO; Zhengkai LI; Baoqing YIN; Hao SUN; Xinghu YU; Jianbin QIU; Weichao SUN

IPC分類

G6F 30/398G6F 115/12

CPC分類

G6F30/398G6F2115/12

The time-optimal placement path optimization method for surface mounters in this invention addresses the issue of excessively long total mounting time and low production efficiency in array-type layout circuit board assembly. This invention divides the placement points on the circuit board into grid rows based on component types and Y-axis coordinates, categorizes the placement points into different grid rows, and performs a global balance search. After identifying the placement points within each grid row that can be mounted simultaneously, it integrates two methods for the initial head-to-point assignment where the “simultaneous placement maximization” method promotes “approximate simultaneous placement” to the greatest extent, and the “progressive search rule” method avoids a purely local greedy search. A general solution framework for placement path optimization is constructed, where based on the initial assignment results, the unassigned remaining placement points are matched using the nearest insertion method, refining and deriving the final optimization result.

原文(中国語)

The time-optimal placement path optimization method for surface mounters in this invention addresses the issue of excessively long total mounting time and low production efficiency in array-type layout circuit board assembly. This invention divides the placement points on the circuit board into grid rows based on component types and Y-axis coordinates, categorizes the placement points into different grid rows, and performs a global balance search. After identifying the placement points within each grid row that can be mounted simultaneously, it integrates two methods for the initial head-to-point assignment where the “simultaneous placement maximization” method promotes “approximate simultaneous placement” to the greatest extent, and the “progressive search rule” method avoids a purely local greedy search. A general solution framework for placement path optimization is constructed, where based on the initial assignment results, the unassigned remaining placement points are matched using the nearest insertion method, refining and deriving the final optimization result.

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