A Review and Analysis of Automatic Optical Inspection and Quality Monitoring Methods in Electronics Industry

数码产品 计算机科学 自动光学检测 软件 人工智能 预处理器 质量(理念) 自动X射线检查 电子元件 特征提取 计算机硬件 图像处理 工程类 电气工程 图像(数学) 哲学 认识论 程序设计语言
作者
Abd Al Rahman M. Abu Ebayyeh,Ali Mousavi
出处
期刊:IEEE Access [Institute of Electrical and Electronics Engineers]
卷期号:8: 183192-183271 被引量:195
标识
DOI:10.1109/access.2020.3029127
摘要

Electronics industry is one of the fastest evolving, innovative, and most competitive industries. In order to meet the high consumption demands on electronics components, quality standards of the products must be well-maintained. Automatic optical inspection (AOI) is one of the non-destructive techniques used in quality inspection of various products. This technique is considered robust and can replace human inspectors who are subjected to dull and fatigue in performing inspection tasks. A fully automated optical inspection system consists of hardware and software setups. Hardware setup include image sensor and illumination settings and is responsible to acquire the digital image, while the software part implements an inspection algorithm to extract the features of the acquired images and classify them into defected and non-defected based on the user requirements. A sorting mechanism can be used to separate the defective products from the good ones. This article provides a comprehensive review of the various AOI systems used in electronics, micro-electronics, and opto-electronics industries. In this review the defects of the commonly inspected electronic components, such as semiconductor wafers, flat panel displays, printed circuit boards and light emitting diodes, are first explained. Hardware setups used in acquiring images are then discussed in terms of the camera and lighting source selection and configuration. The inspection algorithms used for detecting the defects in the electronic components are discussed in terms of the preprocessing, feature extraction and classification tools used for this purpose. Recent articles that used deep learning algorithms are also reviewed. The article concludes by highlighting the current trends and possible future research directions.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
1秒前
HELAOBAN发布了新的文献求助10
1秒前
1秒前
nn发布了新的文献求助10
1秒前
2秒前
曾云璐完成签到,获得积分20
2秒前
Sakura应助enen采纳,获得30
2秒前
wangxianjin20发布了新的文献求助10
2秒前
留胡子的松完成签到 ,获得积分10
3秒前
Lucas应助橘橘采纳,获得10
3秒前
3秒前
一见喜发布了新的文献求助10
4秒前
4秒前
NMSL发布了新的文献求助10
4秒前
在水一方应助shea采纳,获得10
4秒前
科研通AI2S应助gao采纳,获得10
4秒前
Lucas应助肥小耗采纳,获得10
5秒前
研友_LNBayL完成签到,获得积分10
5秒前
清脆迎曼应助哈哈哈哈哈采纳,获得10
5秒前
5秒前
传奇3应助传统的妖妖采纳,获得10
5秒前
勤劳不弱发布了新的文献求助10
5秒前
fish发布了新的文献求助10
5秒前
16494864发布了新的文献求助10
5秒前
万事如意完成签到 ,获得积分10
6秒前
GC完成签到 ,获得积分10
6秒前
eghiefefe完成签到,获得积分10
7秒前
传奇3应助Sunshine采纳,获得10
7秒前
xiuxiu酱完成签到,获得积分10
8秒前
WDK发布了新的文献求助10
8秒前
8秒前
酷酷纸飞机完成签到,获得积分10
9秒前
9秒前
10秒前
wangxianjin20完成签到,获得积分10
10秒前
CC66关注了科研通微信公众号
10秒前
10秒前
10秒前
11秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Fermented Coffee Market 2000
Constitutional and Administrative Law 500
PARLOC2001: The update of loss containment data for offshore pipelines 500
Critical Thinking: Tools for Taking Charge of Your Learning and Your Life 4th Edition 500
Investigative Interviewing: Psychology and Practice 300
Atlas of Anatomy (Fifth Edition) 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5286781
求助须知:如何正确求助?哪些是违规求助? 4439406
关于积分的说明 13821497
捐赠科研通 4321398
什么是DOI,文献DOI怎么找? 2371854
邀请新用户注册赠送积分活动 1367418
关于科研通互助平台的介绍 1330879