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Uncertainty Quantification for Real‑World Model Deployment in Industrial Systems

Ansys

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Overview

As organizations adopt digital twins, predictive maintenance, and model-based control, understanding model uncertainty becomes mission critical. This is especially true for industrial equipment deployed in the field: pumps, HVAC systems, compressors, motors, turbines, and other assets where reliability and uptime matter.

This session shows how to quantify, manage, and communicate uncertainty in deployed models.

What Attendees Will Learn

  • How to prepare simulation models for deployment in digital twins and control systems
  • How to use reduced order and surrogate models without sacrificing credibility
  • How to quantify and monitor uncertainty in deployed models
  • How to integrate UQ into MBSE and system architecture workflows
  • How to verify embedded software and real-time models for production use
  • How to build a long-term roadmap for lifecycle ready model confidence

Who Should Attend

  • Director / Manager of Engineering
  • Director of Technology / New Product Development
  • Electrical Powertrain Engineers
  • Motor/Drive & Controls Engineers
  • CFD / FEA / Mechanical Simulation Engineers
  • Product Managers for Pumps, Compressors, Motors, Drives
  • Systems Engineers & Digital Engineering Leads
  • Innovation / R&D Leaders in Industrial OEMs

Speaker

  • Kaylan C Sharma - Applications Engineering, Manager

Date / Time: April 28, 2026, 9 AM EDT
Venue: Virtual
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