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Quality Control for Smart Manufacturing in Industry 5.0

In: Artificial Intelligence for Smart Manufacturing

Author

Listed:
  • Huu Du Nguyen

    (Dong A University)

  • Phuong Hanh Tran

    (HEC Liège - Management School of the University of Liège)

  • Thu Ha Do

    (ULR 2461 - GEMTEX - Génie et Matériaux Textiles)

  • Kim Phuc Tran

    (ULR 2461 - GEMTEX - Génie et Matériaux Textiles)

Abstract

Smart manufacturing is widely accepted as the new emerging transformation of the manufacturing industry today. In addition, quality control, an important aspect that contributes to the successful process of smart manufacturing attracts attention from the community. However, there are certain challenges in implementing quality control methods in Industry 5.0. Thus, this chapter aims to provide a comprehensive background review of important notions and advanced techniques related to quality control for smart manufacturing such as Machine Learning, computer vision, the Internet of Things, and Artificial Intelligence. Then, several difficulties and opportunities in the implementation of these techniques for quality control in Industry 5.0 are discussed. Finally, a case study on monitoring wine production in the food industry is also considered to show the performance of Machine Learning-based techniques for quality control.

Suggested Citation

  • Huu Du Nguyen & Phuong Hanh Tran & Thu Ha Do & Kim Phuc Tran, 2023. "Quality Control for Smart Manufacturing in Industry 5.0," Springer Series in Reliability Engineering, in: Kim Phuc Tran (ed.), Artificial Intelligence for Smart Manufacturing, pages 35-64, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-031-30510-8_3
    DOI: 10.1007/978-3-031-30510-8_3
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