The 3D printing process often involves trial and error, leading to wasted materials and time. Ptarium aims to streamline this process by integrating AI and machine learning to predict and optimize print outcomes. The goal is to develop a prototype system that can analyze print parameters and suggest optimal settings for various materials and designs. This project will allow learners to apply their knowledge of AI/ML algorithms, data analysis, and 3D printing technology. By focusing on a specific aspect of the printing process, the project ensures a manageable scope that can be completed within the given timeframe. The learners will work on creating a model that can predict potential print failures and suggest improvements, thus removing much of the guesswork involved in 3D printing.

The primary deliverable is a functional prototype of an AI-driven system that can analyze and optimize 3D printing parameters. Additional deliverables include a comprehensive report detailing the system's development process, a presentation demonstrating the system's capabilities, and a set of recommendations for further improvements. The project will culminate in a demonstration of the prototype's effectiveness in reducing errors and improving print quality.