A Deep Learning-based General Defect Detection Framework for Automated Optical Inspection

Chia Yu Lin, Yan Hung Chou, Yun Chiao Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Artificial intelligence (AI) is applied in automated optical inspection (AOI) to help inspect defects and reduce the false discovery rate of AOI in manufacturing industries. In current studies, the training data of AI models are sufficient, and the source data are from the specific production line. However, defect samples are insufficient, and the data source is variant. The current models need more generalization to all machines and take a long training time to build a new model for other appliances. This paper proposes a Deep Learning-based General Defect Detection Framework (DL-GDD) solves the insufficient data issue and the generalization issue of models. We implement a color preprocessing module, a data augmentation module, a data generation module, and four classification models to detect defects and generalize the utilization of DLG-DD. In experiments, we evaluate DLG-DD based on the NEU-CLS and AIdea datasets. The accuracy of DLG-DD is 90%, and the false omission rate and false discovery rate are less than 1%. DLG-DD is a general framework that tackles insufficient data and decreases the false discovery rate of AOI.

Original languageEnglish
Title of host publicationProceedings of the 2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages332-337
Number of pages6
ISBN (Electronic)9798350313635
DOIs
StatePublished - 2023
Event2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2023 - Hybrid, Bali, Indonesia
Duration: 13 Jul 202315 Jul 2023

Publication series

NameProceedings of the 2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2023

Conference

Conference2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2023
Country/TerritoryIndonesia
CityHybrid, Bali
Period13/07/2315/07/23

Keywords

  • Automated optical inspection
  • classification models
  • data augmentation
  • defect detection

Fingerprint

Dive into the research topics of 'A Deep Learning-based General Defect Detection Framework for Automated Optical Inspection'. Together they form a unique fingerprint.

Cite this