5 papers
A Continual Validation, Updating, and Decision-Making Framework for Self-Adaptive Digital Twins via Robust Model Predictive Control: A Case Study in Additive Manufacturing
Yi-Ping Chen, Ying-Kuan Tsai, Vispi Karkaria +3
Digital Twins rely on surrogate models to mirror physical systems in real time, yet these models can degrade as operating conditions evolve, a phenomenon known as concept drift. Ma…
Bootstrapped Control Limits for Score-Based Concept Drift Control Charts
Jiezhong Wu, Daniel W. Apley
Monitoring for changes in a predictive relationship represented by a fitted supervised learning model (i.e., concept drift detection) is a widespread problem in modern data-driven…
A Framework for Supervised and Unsupervised Segmentation and Classification of Materials Microstructure Images
Kungang Zhang, Wei Chen, Wing K. Liu +2
Microstructure of materials is often characterized through image analysis to understand processing-structure-properties linkages. We propose a largely automated framework that inte…
One-at-a-time knockoffs: controlled false discovery rate with higher power
Charlie K. Guan, Zhimei Ren, Daniel W. Apley
We propose one-at-a-time knockoffs (OATK), a new methodology for detecting important explanatory variables in linear regression models while controlling the false discovery rate (F…
Emerging Microelectronic Materials by Design: Navigating Combinatorial Design Space with Scarce and Dispersed Data
Hengrui Zhang, Alexandru B. Georgescu, Suraj Yerramilli +5
The increasing demands of sustainable energy, electronics, and biomedical applications call for next-generation functional materials with unprecedented properties. Of particular in…