🤖 AI-Based System for Optimizing CAD Models

Fraunhofer
Written By RG .

🔧 Tools & Technologies:

Python, Neural Networks, Linux, NuroCAD, AI Agents, Data Annotation, CAD Models, Bowl feeder, Mech

📄 Overview

This project focused on developing an AI-based system for optimizing CAD models to enhance automation processes in assembly. The system was designed to enable neural networks to independently recognize and interpret CAD geometries from a vast database, contributing to faster and more intelligent assembly process.

🎯 Objectives

  • Support the development of an AI-powered system to analyze and optimize CAD models

  • Assist in creating a comprehensive and structured data set for training neural networks

  • Learn and explore AI concepts, neural network programming, and system integration techniques

🧠 What I Did (Role: Project In Charge)

  • Participated in the annotation of training data for NuroCAD’s neural network model

  • Supported the preparation of a large dataset consisting of diverse CAD models

  • Gained exposure to AI systems, neural network architecture, and AI agent behavior

  • Learned the fundamentals of Python programming, Linux environment, and debugging techniques

  • Worked closely with the research team to understand system architecture and integration workflows

RG .
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🔗Main Proj: Integrated Engineering Data Transformation using AutomationML