Towards Applicability of Machine Learning in Quality Control for Smart Manufacturing  
Author Huu Du Nguyen


Co-Author(s) Phuong Hanh Tran; Do Thu Ha; Cédric Heuchenne; Kim Phuc Tran


Abstract In the past decade, industrial manufacturing has made great strides thanks to the application of advantaged technologies such as digital twins, virtual reality, augmented reality, artificial intelligence (AI), the Internet of Things, and computer vision. These technologies have benefited industrial manufacturing, changing its nature from automated to smart. Recently, a new concept of Industry 5.0 has been introduced in the literature, complementing the existing Industry 4.0 by highlighting innovation as a driver for a transition to a sustainable, human-centric and resilient industry. In human-centric manufacturing, the role of QC is becoming more and more important. In this study, we aim to conduct a survey on the advanced methods enabling QC in smart manufacturing in Industry 5.0. We focus on AI-based methods and discuss several challenges and perspectives for AI-based QC for smart manufacturing in Industry 5.0. In addition, a case study about the application of machine learning algorithms in industrial quality control will be presented.


    Article #:  DSBFI23-42
Proceedings of 2nd ISSAT International Conference on Data Science in Business, Finance and Industry
January 8-10, 2023 - Da Nang, Vietnam