Forthcoming Articles

International Journal of Mechatronics and Manufacturing Systems

International Journal of Mechatronics and Manufacturing Systems (IJMMS)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Mechatronics and Manufacturing Systems (One paper in press)

Regular Issues

  • Deep Learning-Based Wafer Fabrication Quality Assessment in Semiconductor Manufacturing   Order a copy of this article
    by Jinxing Zhao, Quan Meng, Haolan Zheng, Yuhao Fan, Zinuo Zeng 
    Abstract: Semiconductor manufacturing relies heavily on wafer fabrication quality, as it directly determines the performance and reliability of downstream electronic and optoelectronic devices. To address the challenges of reliability and efficiency in wafer quality assessment, we propose a deep learning-based multi-label defect detection and classification method for wafer fabrication. The method employs the ShuffleNetV2 for feature extraction, and the Sigmoid activation function for multi-label outputs. The CB-Focal Loss was introduced to tackle class imbalance while the coordinate attention mechanism was integrated to enhance the model's focus on defect regions. Experiments on our own AFM-Wafer dataset demonstrate that, compared with the baseline model, new model achieves 0.51%, 1.39%, 1.31%, and 1.24% increases in Accuracy, L-Precision, L-Recall and L-F1 score, respectively while maintaining nearly the same parameter count and inference speed. This research demonstrates how advanced computer vision and deep learning complement traditional manufacturing and economic merits.
    Keywords: Wafer Fabrication; Deep Learning; Defect Detection; Quality Assessment; Semiconductor Manufacturing.
    DOI: 10.1504/IJMMS.2025.10077423
     

 

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