Industry 4.0, characterized by the incorporation of AI, robotics, 3D printing, and the Industrial Internet of Things (IIoT), is transforming manufacturing by enhancing efficiency, quality control, and supply chain management. At the Perceive 2020 conference, Qian Lin, Ph.D. of HP, highlighted the role of deep learning in automating visual inspection processes for quality control, which significantly reduces inventory and time to market. The advancements in deep learning are driven by large datasets, better network models, and powerful GPUs, enabling automation in quality control by utilizing computer vision. This technology is particularly beneficial for custom production, where manual inspections are challenging due to high error rates and costs. HP's application of AI in their printing processes exemplifies how simulated defects are used for training AI models, improving print defect characterization. These advancements reflect a shift from "classical" rule-based computer vision to deep-learning-driven automation, which is expected to extend beyond 2D image quality control to other production systems, facilitating mass customization and reducing delays in quality assurance.