An ML-aided Approach to Automatically Generate Schematic Symbols in PCB EDA Tools

The traditional manual drawing method of creating schematic symbols in current PCB EDA software is tedious and time-consuming. To address this problem, this paper proposes an ML-aided approach that can generate schematic symbols automatically and quickly. The approach effectively addresses the critical challenges of pin number-name pairing and direction recognition in package diagrams. Currently, the proposed approach supports both double-side and four-side symbol generation with high accuracy and efficiency. Compared to the traditional manual method taking several minutes to hours, the proposed ML-aided approach can generate a schematic symbol within one to two minutes.

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Publication Details

Published
2024-09-03
DOI
https://doi.org/10.1145/3670474.3685944
Primary Topic
Handwritten Text Recognition Techniques
Type
article
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article

An ML-aided Approach to Automatically Generate Schematic Symbols in PCB EDA Tools

Keni Qiu, Shiyu Gao
Handwritten Text Recognition Techniques
article

An ML-aided Approach to Automatically Generate Schematic Symbols in PCB EDA Tools

Keni Qiu, Shiyu Gao
article en

Abstract

The traditional manual drawing method of creating schematic symbols in current PCB EDA software is tedious and time-consuming. To address this problem, this paper proposes an ML-aided approach that can generate schematic symbols automatically and quickly. The approach effectively addresses the critical challenges of pin number-name pairing and direction recognition in package diagrams. Currently, the proposed approach supports both double-side and four-side symbol generation with high accuracy and efficiency. Compared to the traditional manual method taking several minutes to hours, the proposed ML-aided approach can generate a schematic symbol within one to two minutes.

Capital Normal University (CN)
Openalex Percentile: Top 86%
Handwritten Text Recognition Techniques
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