Composite lay-up
Assembly Line
Large language model based agent for process planning of fiber composite structures
Process planning is a crucial activity, connecting product development and manufacturing of fiber composite structures. Recently published Large Language Models (LLM) promise more flexible and autonomous workflows compared to state of the art automation methods. An autonomous agent for process planning of fiber composite structures is implemented with the LangChain framework, based on OpenAI’s GPT-4 language model. The agent is equipped with deterministic tools which encode a-priori process planning knowledge. It can handle different process planning problems, such as cycle time estimation and resource allocation. Combinations thereof are solved through executing a multi-step solution path.
The agent is supposed to solve these problems autonomously:
- Time Estimation - Estimate the cycle time, i.e., duration from start to end, for a manufacturing task.
- Process Chains - Determine which tasks are required in which order to manufacture a specific component.
- Resource Allocation - Identify the resources, e.g. machines, required to manufacture a specific component.
- Integrated Planning - Estimate the total cycle time for a chain of tasks required to manufacture a component.
How Fives Group is Changing Composite Lay-Up with RoboDK
Composite lay-up (a core step in the process of making a composite part) is traditionally a labor-intensive process. The process requires skilled technicians to create the parts needed using specialized tools and equipment. This is often slow and expensive, which limits the quantity of parts that composite manufacturers can make.
The Composites & Automated Solutions group at Fives has developed a technology that allows their customers to create composite parts using a robotic fiber placement head. This technology provides a lower-cost entry point into the composite lay-up process, making it easier for manufacturers to create the parts they need.