3D Printer Materials Prediction
Project Complexity - Intermediate
Technology: Machine Learning | Business Sector: Smart Cities
Project Description
Predicting material would be more suitable for making the 3D model. In this project the input parameters are like Layer Height (mm),Wall Thickness (mm),Infill Density (%),Infill Pattern (honeycomb, grid),Nozzle Temperature (Cº),Bed Temperature (Cº),Print Speed(mm/s),Fan Speed (%), Roughness (µm),Tension (ultimate), Strength (MPa),Elongation (%).Based on these parameters a supervised machine learning model is built to predict the best material to be used for building 3D models
Solution:
Predicting material would be more suitable for making the 3D model. In this project the input parameters are like Layer Height (mm),Wall Thickness (mm),Infill Density (%),Infill Pattern (honeycomb, grid),Nozzle Temperature (Cº),Bed Temperature (Cº),Print Speed(mm/s),Fan Speed (%), Roughness (µm),Tension (ultimate), Strength (MPa),Elongation (%).Based on these parameters a supervised machine learning model is built to predict the best material to be used for building 3D models. A web application is built so that the user can type in the mentioned parameters and the material which suits them best is showcased on UI
