Publications Internationales

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Author: search.filters.author.Gaceb, MohamedHas files: No

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    Smart casting: vision-driven defect detection for high-precision manufacturing
    (Springer Science and Business Media, 2025) Sabri, Khier; Gaceb, Mohamed
    This study introduces a vision-driven defect detection system leveraging advanced deep learning architectures to enhance quality control in metal manufacturing. The system integrates four models: the VGG-19 Network, an Attention-Augmented Convolutional Neural Network (CNN), a Vision Transformer (ViT), and a Convolutional Autoencoder. These models were trained and evaluated on a dataset of annotated high-resolution images of impellers acquired under controlled industrial conditions. Among the classifiers, the VGG-19 Network achieved an overall classification accuracy of 100% on this dataset, with F1-scores of 100% for defective samples and 99% for acceptable ones. Grad-CAM visualizations were used to highlight the critical regions influencing the VGG-19 network’s classification decisions. The Attention-Augmented CNN achieved an accuracy of 98.17%. The ViT model yielded F1-scores of 99.42% on the training set and 100% on the validation set, with a 0% false positive rate and a 1.54% false negative rate. The Convolutional Autoencoder enabled unsupervised segmentation by detecting pixel-wise reconstruction errors that indicate anomalies. Each of the four models exhibits an acceptable level of performance with respect to both computational efficiency and deployment feasibility for real-time anomaly detection in manufacture processes
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    Using a supperficially treated 2024 aluminum alloy drill pipe to delay failure during dynamic loading
    (Elsevier, 2019) Belkacem, Lallia; Abdelbaki, Noureddine; Otegui, Jose Luis; Gaceb, Mohamed; Bettayeb, Mourad
    For many years, a critical factor while drilling deep wells in Algeria oil fields has been the fatigue loads in drill strings used in high tortuosity sections. One solution is the use of drill pipes made of alternative lighter materials instead of conventional steel. A thorough study of superficially (ST) treated 2024 aluminum alloy joined to steel drill pipes in crooked well trajectories is presented in this article. This work discusses several limiting loads exerted on the drill pipes that affect the drilling operation such as axial, twisting and bending forces, which lead to combined cyclic loads. This study is aimed to determine whether it is possible to extend the drilling operation by joining ST 2024 aluminum alloy drill pipes into the drilling string, without losing drilling stability or reliability. It is established that the ST 2024 aluminum alloy drill pipe exerts significant influence on the allowable combined load, but affects to a larger extent the critical load at which loss of drilling string stability occurs, along with improved resistance to wear and corrosion, even at high temperature