Generative Design is a cutting-edge, AI-driven approach that transforms the way we conceptualize and create engineering solutions. Instead of manually modeling a structure based on past experience or intuition, engineers define the design goals, constraints, material properties, manufacturing methods, and loading conditions and the software explores hundreds or even thousands of optimized design alternatives.

This iterative and exploratory process mimics nature's evolutionary approach, using algorithms to evaluate and evolve solutions based on performance metrics such as strength, weight, durability, and cost-efficiency.

Unlike traditional CAD modeling, where design originates from the engineer’s mind, generative design starts with data — and ends with innovation.

𝟮𝟬𝟮𝟱–𝟮𝟬𝟮𝟳: 𝘐𝘯𝘵𝘦𝘭𝘭𝘪𝘨𝘦𝘯𝘵 𝘗𝘳𝘰𝘤𝘦𝘴𝘴 𝘊𝘰𝘯𝘵𝘳𝘰𝘭
Real-time manufacturing optimization using AI, adaptive systems, and optical sensors.

𝟮𝟬𝟮𝟳–𝟮𝟬𝟮𝟴: 𝘚𝘶𝘴𝘵𝘢𝘪𝘯𝘢𝘣𝘪𝘭𝘪𝘵𝘺 & 𝘏𝘶𝘮𝘢𝘯 𝘞𝘦𝘭𝘭-𝘣𝘦𝘪𝘯𝘨
Focus on eco-friendly processes, bio-compatible materials, and socially responsible production.

𝟮𝟬𝟮𝟴–𝟮𝟬𝟯𝟬: 𝘈𝘥𝘷𝘢𝘯𝘤𝘦𝘥 𝘏𝘶𝘮𝘢𝘯-𝘔𝘢𝘤𝘩𝘪𝘯𝘦 𝘐𝘯𝘵𝘦𝘳𝘧𝘢𝘤𝘦𝘴 (𝘈𝘏𝘔𝘐)
Integration of AR/MR for immersive monitoring and co-creation in AM.

2030–2032: 𝘊𝘺𝘣𝘦𝘳-𝘗𝘩𝘺𝘴𝘪𝘤𝘢𝘭 𝘚𝘦𝘤𝘶𝘳𝘪𝘵𝘺 & 𝘙𝘦𝘴𝘪𝘭𝘪𝘦𝘯𝘤𝘦
Robust and secure AM environments via AI-driven anomaly detection and system integration.

In this example, we explore new design ideas faster by leveraging existing models. ⚡️
In recent projects, we ran up to 250 training samples of various bracket designs to develop a comprehensive AI model. Using SimAI, we can predict physical behaviors such as Von Mises stress in seconds.
And here's the exciting part: Each prediction from the AI comes with a confidence level, shown to increase with the number of training samples.

𝘉𝘳𝘦𝘢𝘬𝘵𝘩𝘳𝘰𝘶𝘨𝘩𝘴, 𝘪𝘯𝘴𝘪𝘨𝘩𝘵𝘴, 𝘢𝘯𝘥 𝘳𝘦𝘢𝘭-𝘸𝘰𝘳𝘭𝘥 𝘪𝘯𝘯𝘰𝘷𝘢𝘵𝘪𝘰𝘯𝘴 𝘧𝘳𝘰𝘮 𝘨𝘭𝘰𝘣𝘢𝘭 𝘭𝘦𝘢𝘥𝘦𝘳𝘴 𝘭𝘪𝘬𝘦 𝘕𝘈𝘚𝘈, 𝘎𝘌, 𝘢𝘯𝘥 𝘙𝘰𝘭𝘭𝘴-𝘙𝘰𝘺𝘤𝘦.

𝗪𝗶𝘁𝗵 𝘁𝗵𝗶𝘀 𝗰𝗼𝗺𝗯𝗶𝗻𝗲𝗱 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵, 𝗺𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗲𝗿𝘀 𝗰𝗮𝗻 𝗻𝗼𝘄:
🔹 Program and simulate #robot operations offline — reducing downtime and human error
🔹 Predict system-level risks before execution — using #AI models trained on historical data and #system behavior
🔹 Detect potential collisions, failure modes, or abnormal loads early in the workflow
🔹 Ensure higher #safety, efficiency, and #quality — even in complex, high-mix production environments

𝗔𝗱𝗱𝗶𝗧𝗲𝗰𝗵 is building the future of metal additive manufacturing with real-time AI-based monitoring, using thermal and optical sensors to detect defects like porosity and LOF as they happen.

🔍 Get ready to experience the future of metal 3D printing! We’re excited to introduce our ground‑breaking UDI Model 01, an AI-powered Intelligent Monitoring System that transforms real‑time quality control and adaptive process management.

Join us on this innovation journey from the heart of Turin and be part of the future of additive manufacturing!

#AddiTech #3DPrinting #AI #SmartManufacturing #Innovation

🌐 Learn more: AddiTech's LinkedIn Page
📩 Contact us: Alirezaghiasvandpolito@gmail.com
@AddiTech

Unlike standard YOLO detection, I've extended the functionality to approximate distance using object position in the frame - giving a pseudo-depth insight using just 2D vision. Think of it like the first step toward monocular ADAS systems.
Built on YOLOv8x-seg from Ultralytics for fine-grained object masks.

Project DIAMOnD helps small manufacturers access 3D printing technology through shared facilities, training, and networked printers.

Bifrost Manufacturing combines machining, welding, and fabrication with a growing focus on additive manufacturing to meet diverse customer needs.

MHowco Additive operates inside a larger company focused on distributing large metal products, but is carving out new opportunities in 3D printing.

Knust Godwin, originally a precision machining company, now integrates metal additive manufacturing to complement its existing capabilities.