<p>Since the advent of Industry 4.0, the global manufacturing industry has been rapidly transitioning beyond simple automation to a human-centered, intelligent manufacturing system where machines, men, and materials are seamlessly integrated. This paper presents research trends in workforce augmentation and plug-and-produce process equipment autonomous control using physical artificial intelligence, which plays a key role in this transition. As the approach for workforce augmentation, smart human-machine interface mitigated the knowledge gap among on-site workers and integrating training with real-time task assistance. The interface system included a manual chatbot trained on machine tool manuals and alarm information by using large language models, and a persona-in-the-loop copilot framework that adjusts the level of explanation based on the worker’s skill level and role. Beyond the human intervention, the plug-and-produce process autonomous control technologies integrated with robots, machine tools, and automation controllers. These included robot task learning combining the vision-language-action model and digital twins, collaborative control of multiple robots and sensors using the asset administration shell and multi-agent framework, automatic control program conversion between heterogeneous controller, and automatic part program generation based on group technology. The proposed system showed an integrated approach to apply generative AI across the entire human-robot-equipment control chain.</p> Graphical Abstract <p></p>