AI & Informatics

MAR-AM is a web-based automated ML-assisted manufacturability analyzer and recommender for AM. This tool can serve as a first-level evaluation of designs for novice AM users such as designers to determine whether their given design is printable through their selected printer. As an ongoing project developed at McGill’s Additive Design & Manufacturing Laboratory (ADML), it has been a valuable research tool. By giving full access to the source, we hope this tool can be useful to lower the threshold of AM processes and support wider applications of AM in the future.

The MLACCD software is designed based on the python tkinter GUI library, and powered by the tensorflow. It contains models of MLACCD implementation, and an expandable design data base. This software provides a user-friendly interface that guide the researchers and industrial users to create their own MLACCD channels with desired conformal cooling topologies to minimize the resulting part surface temperature and increase the part quality.

This is an interactive knowledge database for Multifunctional Bio-inspired Design (MBID) Ideation System

SciHIT IE (Scientific Human–AI Teaming for Information Extraction) is a human-centered framework designed to extract structured scientific information from literature using large language models (LLMs). It combines automated natural language processing with expert-in-the-loop feedback to ensure accuracy, transparency, and adaptability.

DeepBead supports the on-machine integration of video-based deep learning models for defect detection during the additive manufacturing of metal matrix composites (MMCs). It can be deployed on industrial machines to support both R&D activities and production by providing near real-time analysis of monitoring data. The current version supports the integration of up to two monitoring systems and the detection of up to six different co-existing anomalies in the microstructure of MMCs. To enhance the analysis of monitoring data, predictions from individual video models can be fused for more effective defect detection.