AI Update in Additive Manufacturing: Design, Process, Workforce and Industry impact

Fabian Alefeld hosts Duann Scott on the Editor Snack podcast to discuss how AI is evolving in additive manufacturing, moving from “AI-washing” and impractical text-to-mesh hype toward more capable tools using language models, visual language models, surrogate models, and emerging foundational models. Scott describes testing tools by trying to make them fail and highlights a recent success with the Raven plugin for Rhino/Grasshopper, which generated a parametric VESA mount and tripod adapter from minimal prompts, then iteratively added fillets and an isogrid structure and produced a printable part within hours. They discuss constraints like missing engineering training data and design intent, the promise of AI for toolpath and process optimization (including transfer of parameter knowledge across materials), and the role of the 3MF format in capturing toolpath and metadata to enable richer, searchable datasets. Scott previews CDFAM events in Barcelona, DC, and Tokyo and emphasizes that progress requires significant data work and investment.

00:00 Welcome and Guest Intro

02:18 AI Hype to Real Progress

04:13 Testing AI Design Tools

04:46 Data Gaps and Design Intent

07:15 Two Paths for AI Design

10:15 Raven Grasshopper Breakthrough

13:17 Pushing Parametric Complexity

20:28 Limits of Black Box Optimization

22:40 Toolpath and Material Transfer

26:18 Alloy Discovery and Qualification

28:05 3MF Role Teaser

28:18 3MF Format Overview

29:17 Smarter Toolpath Extensions

32:31 Metadata for AI Training

35:43 Data Ownership and Synthetic Data

39:59 AI Impact on Additive

44:10 Workforce and Reshoring

47:22 What Is CDFAM

49:49 CDFAM Audience and Format

51:43 DC Event and Government

54:05 Wrap Up and Thanks