The project focuses on developing a machine learning AI model to optimize materials and processes in additive manufacturing. Additive manufacturing, or 3D printing, is revolutionizing production by allowing for complex designs and reduced material waste. However, optimizing the materials and processes involved is crucial for improving efficiency and product quality. The goal is to create a predictive model that can suggest optimal material compositions and process parameters, reducing trial-and-error in manufacturing. This project offers learners the chance to apply their knowledge of machine learning, data analysis, and materials science to a real-world problem. By working on this project, students will gain insights into the intersection of AI and manufacturing, preparing them for future roles in the industry.

The deliverables for this project include a functional machine learning model capable of predicting optimal materials and process parameters for additive manufacturing. Additionally, a comprehensive report detailing the model's development process, data used, and validation results will be required. A presentation summarizing the findings and demonstrating the model's application in a manufacturing scenario will also be part of the deliverables.