A new study highlights the limitations of global anomaly detection models in multi-product manufacturing environments, which can overlook subtle anomalies and cyber-attacks. The proposed Product-Aware Autoencoder demonstrates improved detection accuracy and robustness by focusing on product-specific data distributions, suggesting a shift towards more tailored diagnostic systems in Industry 4.0.