SolderNet: Towards trustworthy visual inspection of solder joints in electronics manufacturing using explainable artificial intelligence

IF 2.5 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Ai Magazine Pub Date : 2023-10-15 DOI:10.1002/aaai.12129

Hayden Gunraj, Paul Guerrier, Sheldon Fernandez, Alexander Wong

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引用次数: 0

Abstract

In electronics manufacturing, solder joint defects are a common problem affecting a variety of printed circuit board components. To identify and correct solder joint defects, the solder joints on a circuit board are typically inspected manually by trained human inspectors, which is a very time-consuming and error-prone process. To improve both inspection efficiency and accuracy, in this work, we describe an explainable deep learning-based visual quality inspection system tailored for visual inspection of solder joints in electronics manufacturing environments. At the core of this system is an explainable solder joint defect identification system called SolderNet that we design and implement with trust and transparency in mind. While several challenges remain before the full system can be developed and deployed, this study presents important progress towards trustworthy visual inspection of solder joints in electronics manufacturing.

Abstract Image

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SolderNet：利用可解释人工智能实现电子制造中焊点的可信视觉检测

在电子制造过程中，焊点缺陷是影响各种印刷电路板组件的常见问题。为了识别和纠正焊点缺陷，电路板上的焊点通常由训练有素的人工检测人员进行人工检测，这是一个非常耗时且容易出错的过程。为了提高检测效率和准确性，我们在这项工作中介绍了一种基于可解释深度学习的视觉质量检测系统，该系统专为电子制造环境中的焊点视觉检测而定制。该系统的核心是一个名为 SolderNet 的可解释焊点缺陷识别系统。虽然在开发和部署完整系统之前仍存在一些挑战，但本研究为电子制造领域值得信赖的焊点视觉检测取得了重要进展。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Ai Magazine 工程技术-计算机：人工智能

CiteScore

3.90

自引率

11.10%

发文量

审稿时长

>12 weeks

期刊介绍： AI Magazine publishes original articles that are reasonably self-contained and aimed at a broad spectrum of the AI community. Technical content should be kept to a minimum. In general, the magazine does not publish articles that have been published elsewhere in whole or in part. The magazine welcomes the contribution of articles on the theory and practice of AI as well as general survey articles, tutorial articles on timely topics, conference or symposia or workshop reports, and timely columns on topics of interest to AI scientists.