This project explores how Generative AI can be used to identify defects in Additive Manufacturing (AM)-produced parts.
Agent-based systems have revolutionized industries such as communication, business, and manufacturing by providing adaptability, scalability, and real-time decision-making in complex environments. In manufacturing, they automate tasks ranging from product design to supply chain management to support the basic principles of Industry 4.0. Traditional agents, while precise and reliable for structured tasks, face limitations in flexibility and adaptability to dynamic or unstructured environments. A new type of agent, a Generative Artificial Intelligence (GenAI) agent will dramatically alter the landscape of agent-based systems by offering versatility, adaptability, contextual understanding, and the ability to handle unstructured data. Powered by increasingly sophisticated GenAI models, GenAI agents will integrate multiple roles, enhance automation, and introduce capabilities beyond the scope of traditional agents. This paper explores how GenAI agents will improve upon the tasks performed by traditional agents and introduce new functionalities to establish themselves critical enablers for modern manufacturing ecosystems.
The wrok is a collaboration of myself, Paul withrell, Maja Vukovic and Soundar Kumara .