Adapting automated manufacturing to accommodate new product designs is often challenging in traditional manufacturing systems. Plug & Produce is a concept that enables for faster adaptation to new product requirements. Research has shown that this can be done through standardized, modular resources that can be easily reconfigured and moved around. However, new flexible approaches are needed to make these modules work together with the automation control system. Typically, these changes to automation requires re-programming or advanced reconfigurations. This article presents an approach using Large Language Models to simplify the steps to instruct a Plug & Produce system on what to do.

The aim is to make use of inhouse knowledge, rather than external experts for adapting the manufacturing system to new product designs. It is identified that simulations are important tools for evaluating the generated instructions before deploying them to a physical system. The proposed system is implemented and the result in this article shows that automated manufacturing can be adapted by using a natural language.