AI-Assisted Design Validation Workflow

The disciplined way to put AI inside design verification: where AI genuinely accelerates, where it must be checked against verified physics, and how signed, auditable analysis replaces black-box output.

Private cohorts & on-site
Format: 2-day (8:30 a.m.–4:30 p.m.)
Level: Advanced
Location: Scheduled on demand · on-site at your facility or a regional venue
Date(s): Not yet scheduled for open enrollment. Get notified when it is, or book it privately for your team.
Includes: Certificate of Completion · printed slide binder · take-home reference text

Get notified when this course is scheduled

One email when dates are set. Or skip the wait: run it as a private cohort, on-site at your plant.

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Faculty

Faculty details for this seminar will be announced with the full schedule.

Fees

Early: $1,895 (payment 4+ weeks ahead)
Standard: $2,095 (check/ACH) · $2,165 (card)

Group discount: $200 off per attendee for 3+ from the same organization.

Also Available

  • Corporate on-site delivery at your facility
  • Private cohort sessions
  • Digital curriculum licensing

Seminar Overview

AI can accelerate design validation dramatically — and silently mislead teams that cannot check it. This course teaches the ETS workflow for AI-assisted validation: where AI genuinely outperforms (surrogate screening, geometry exploration, report generation), where it must be verified against physics, and how the Applied Physics Engine and the platform's verification layer turn output into signed, auditable engineering.

The course runs a real part through the full loop: AI-assisted analysis, verification against verified calculation modules, DFM and compliance checks, and the cryptographic signing and immutable audit trail that make results defensible in design reviews and audits. Attendees leave able to deploy the workflow inside their own organization — with the honest boundaries drawn.

Ideal Learner

  • Senior design and CAE engineers who will run AI-assisted validations
  • Engineering leaders accountable for analysis sign-off and audit defense
  • Quality and compliance engineers in regulated industries
  • Teams evaluating AI validation vendors and their claims

Learning Objectives

  • Classify which validation tasks AI accelerates and which require verified physics
  • Run the AI Design Validation workflow end-to-end on a real part
  • Verify AI results against verified calculation modules
  • Produce signed, auditable analysis with the platform trust layer
  • Draw and defend the boundary between AI suggestion and engineering decision

Consulting Sessions

Seminar attendees can sign up for individual consulting sessions with the instructor. Sessions are free for registered attendees, first-come first-served — sign up when registering by calling 248-539-0473 or during the seminar.

Seminar Outline

  • Surrogate screening and geometry exploration
  • Report generation and documentation lift
  • Failure modes of AI analysis: plausible but wrong
  • The verification-first operating rule
  • AI-assisted stress, thermal, and fatigue screening
  • Cross-checking against verified calculation modules
  • DFM and compliance gate checks
  • Escalation: when to insist on full simulation or test
  • Cryptographic signing of engineering analyses
  • The immutable compliance ledger and audit trail
  • Presenting results in design reviews and audits
  • Case pattern: defending an AI-assisted validation
  • Mapping your current verification process onto the loop
  • Roles, gates, and tool access
  • Pilot design and success metrics
  • What good looks like 90 days in

More in Track K — Platform, AI & IT Enablement

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