- Date：Sep 30, 2026
- Location： Online
- Time： 11:30 AM IST
| Date | Time | |
| September 30, 2026 | 14:30 PM IST | Register |
🚀 From DOE to AI: Smarter Molding Process Optimization with Moldex3D
Explore How DOE and AI Can Help Optimize Molding Process Parameters Smarter and Faster
Injection molding process optimization often involves evaluating multiple process parameters and understanding how they affect part quality and molding performance.
Join us to explore how Design of Experiments (DOE) and AI Optimization in Moldex3D can support a smarter and more efficient approach to process optimization. Learn how to systematically evaluate multiple parameters, identify key factors, and explore optimized molding conditions through simulation.
🧠What You’ll Discover
- Introduction to Design of Experiments (DOE) for molding process optimization
- How DOE helps identify key process parameters and their interactions
- Understanding Standard DOE and Taguchi Orthogonal Arrays
- Introduction to AI Optimization and its iterative learning methodology
- Understanding the differences between Standard DOE and AI Optimization
- How to select the right approach for smarter process optimization
🧠Why Attend?
✔ Understand how to systematically optimize multiple molding process parameters
✔ Explore the benefits of DOE for identifying critical factors and interactions
✔ Learn how AI Optimization can support a smarter and more efficient optimization workflow
✔ Gain insights into selecting between DOE and AI Optimization based on your application
Join us and discover how Moldex3D combines DOE and AI to enable smarter, faster, and more efficient molding process optimization
Contact
For sales & technical inquiries, please write to Khaled EL Bchiri at khaled.bchiri@moldex3d.com