Quantum Computing for Simulation in Manufacturing
summary
Project QUASIM develops two concrete prototypes: a milling simulator that converts finite‑element mass and stiffness matrices into a Hermitian operator and uses quantum phase estimation to extract eigenfrequencies so cutters avoid resonance, and a laser‑cutting predictor that combines a graph neural network with a 4‑qubit variational embedding (x,y,z,temperature) following Lloyd/Xanadu encoding. Implementation runs on PennyLane and Qiskit in the lab, shows a small advantage over equivalent MLPs, and prepares first hardware runs on IBM (possible D‑Wave tests).
AI-written summary · about
chapters (15)
- 0:00Introduction
- 1:09Welcome
- 1:37Milling
- 2:19Laser Cutting
- 3:14Current Situation
- 4:24Project QOM
- 5:05Element Method
- 6:23Two Routes
- 6:44Milling Use Case
- 7:40Jet Engine Blades
- 12:55Summary
- 13:22Hybrid Approach
- 15:55Physics Informed Approach
- 16:27Outlook
- 16:59Conclusion
related talks
21mSoftware for Quantum Computing- Easing Solutions for Complex
19mSupporting End-Users in Realizing Quantum Computing Applications
47mUnboxing Quantum Computing
21mHybrid Quantum Computing for AI
16mModeling Heat Flow in Automotive Industry with Novel Quantum Computing Solutions
53mThe quantum computers are coming
22mSchrödinger’s Cat in Industry: Real Life Quantum Software Engineering
38mFacing the Future: A Discussion and Reality Check on Quantum Computing Applications