Uncertainty Quantification for Real‑World Model Deployment in Industrial Systems

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