Research Thrust

AI-Enabled Process Optimization & Control

 

Our research spans the manufacturing enterprise: the process, the asset, the people, and the operation. Each thrust is framed the same way: the operational gap, the research innovation, and the value to industry.

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AI-Enabled Process Optimization & Control

Turning process data into decisions that keep quality within specifications

Edit AI-Enabled Process Optimization & Control

What it means

Modeling approaches that transform data into decisions that improve quality, reduce variation, accelerate process and material understanding, and support control.

Why it matters

Many inspection systems still rely on manual review, fixed thresholds, or generic tools that miss subtle defects in complex production data, so deviations propagate across stations before they are caught and become costly to correct. High-fidelity simulations are often too slow to guide real-time optimization, leaving manual adjustments that are inefficient and non-optimal.

In-Situ Monitoring and Anomaly Detection
Quality Feedback Control
AI-Driven Materials Characterization
Digital Twins and Surrogate Modeling
Additive Manufacturing Qualification and Control

What this research enables

  • In-Situ Monitoring and Anomaly Detection: real-time detection of subtle, high-dimensional defects, scaling across products and lines. 
  • Quality Feedback Control: closing the loop from in-process sensing to correction before deviations propagate.
  • AI-Driven Materials Characterization: microscopy and microstructure images into quantitative, repeatable measurements.
  • Digital Twins and Surrogate Modeling: fast, faithful surrogates that make high-fidelity physics usable in real time.
  • Additive Manufacturing Qualification and Control: Using in-situ sensing, digital twins, and AI to improve 3D/4D printing

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Have a Problem in One of These Areas?

 

Every thrust in this portfolio began with an operational gap a partner needed closed. Tell us about yours.

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