Cutting Physical Test Cycles with Engineering AI

Physical rig testing is slow and expensive, and much of it re-confirms behaviour the team has effectively seen before.

By training surrogate models on years of historical test data, engineers could predict outcomes for many new configurations with quantified confidence.

Low-uncertainty cases were signed off on the model's prediction; only genuinely novel or high-risk cases went to the rig, trimming the test plan without lowering confidence.