A large manufacturing decision model for human-centric decision-making

To adapt to changing demands and disruptions, manufacturing systems necessitate dynamic reconfiguration, facilitated by growing digitalization, modularity, and autonomy. Such reconfiguration, however, heightens decision-making complexity and the need for human supervision. While Generative AI (GenAI), particularly large language models (LLMs), fosters natural human-resource interactions, existing methods lack manufacturing-specific context. This paper introduces a Large Manufacturing Decision Model (LMDM) leveraging image generative models to precisely represent and generate manufacturing-specific reconfiguration decisions using a digital twin, minimizing data requirements and reducing hallucination risks. Simulation results showcase LMDM's ability to refine system configurations through human guidance, transforming digital twins into human-centric decision-making tools.