The machining parameters team’s research focuses on developing a chatbot that enhances user experience and safety within the makerspace, particularly in setting feed speeds for the industrial machines. Our research explores how AI-driven software can simplify machine operation, reduce errors, and make the Makerspace more accessible to users of all skills levels.
For the Spring 2025 semester, our primary objective is developing the chatbot designed specifically around the water jet machine. It will feature a React-based front-end, allowing users to input their specifications and requirements. In the backend, the chatbot will call a REST API that consists of Meta Llama 3.2 to converse with the user and a python function that takes in chart data from AWS DynamoDB, where we store essential machining parameters.
Our approach involves the digitization and restructuring of physical charts and manuals used within the Makerspace to a comprehensive set of data. By converting these static resources into machine-readable formats, we enable real-time data retrieval for optimal machining setting.
Looking ahead, we aim to expand the chatbot’s functionality to support additional machines, including laser cutters, bandsaws, and lathes. We also plan to integrate advanced features such as image recognition, where users can upload photos of materials and desired modifications, allowing the chatbot to provide a list of step-by-step instructions for the user to get their objective done. Through such iterations of our project, we seek to eliminate entry barriers for beginner to intermediate Makerspace users, enhancing the accessibility of the Makerspace for all.
