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Comparison of deep feature extraction for quality prediction in injection molding Cover

Comparison of deep feature extraction for quality prediction in injection molding

Production Engineering Archives
Volume 32 (2026): Issue 1 (March 2026)
By: VietHung Nguyen,  HongSon Nguyen,  TienDung Hoang,  TrongMai Nguyen,  NgocTan Tran and  DinhToan Vu  
Open Access
|Mar 2026

Authors

VietHung Nguyen

nguyenviethung@haui.edu.vn

School of Mechanical & Automotive Engineering, Hanoi University of Industry, Hanoi, Vietnam

HongSon Nguyen

nguyenhongson@haui.edu.vn

HaUI Institute of Technology Hanoi University of Industry, Hanoi, Vietnam

TienDung Hoang

tiendunghaui@gmail.com

School of Mechanical & Automotive Engineering, Hanoi University of Industry, Hanoi, Vietnam

TrongMai Nguyen

trongmai85@gmail.com

School of Mechanical & Automotive Engineering, Hanoi University of Industry, Hanoi, Vietnam

NgocTan Tran

ngoctan82haui@gmail.com

School of Mechanical & Automotive Engineering, Hanoi University of Industry, Hanoi, Vietnam

DinhToan Vu

Toan_vd@haui.edu.vn

School of Mechanical & Automotive Engineering, Hanoi University of Industry, Hanoi, Vietnam
DOI: https://doi.org/10.30657/pea.2026.32.8 | Journal eISSN: 2353-7779 | Journal ISSN: 2353-5156
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Language: English
Page range: 96 - 102
Submitted on: Sep 11, 2025
|
Accepted on: Jan 10, 2026
|
Published on: Mar 9, 2026
Published by: Quality and Production Managers Association
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Deep feature,
Product quality,
Injection moulding,
Autoencoder,
Monitoring
Related subjects:
Business and economics,
Business management,
Business management, other,
Engineering,
Mechanical engineering,
Production technology,
Process engineering and industrial engineering,
Materials sciences,
Materials sciences, other

© 2026 VietHung Nguyen, HongSon Nguyen, TienDung Hoang, TrongMai Nguyen, NgocTan Tran, DinhToan Vu, published by Quality and Production Managers Association
This work is licensed under the Creative Commons Attribution 4.0 License.

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