1 citations · 1 across the 4 of their papers we have counts for
6 papers
Generative Model Predictive Control in Manufacturing Processes: A Review
Suk Ki Lee, Ronnie F. P. Stone, Max Gao +3
Manufacturing processes are inherently dynamic and uncertain, with varying parameters and nonlinear behaviors, making robust control essential for maintaining quality and reliabili…
MP-GFormer: A 3D-Geometry-Aware Dynamic Graph Transformer Approach for Machining Process Planning
Fatemeh Elhambakhsh, Gaurav Ameta, Aditi Roy +1
Machining process planning (MP) is inherently complex due to structural and geometrical dependencies among part features and machining operations. A key challenge lies in capturing…
Physics-Informed Neural Networks For Semiconductor Film Deposition: A Review
Tao Han, Zahra Taheri, Hyunwoong Ko
Semiconductor manufacturing relies heavily on film deposition processes, such as Chemical Vapor Deposition and Physical Vapor Deposition. These complex processes require precise co…
A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components
Fatemeh Elhambakhsh, Daniele Grandi, Hyunwoong Ko
The conceptual design phase represents a critical early stage in the product development process, where designers generate potential solutions that meet predefined design specifica…
Generative Machine Learning in Adaptive Control of Dynamic Manufacturing Processes: A Review
Suk Ki Lee, Hyunwoong Ko
Dynamic manufacturing processes exhibit complex characteristics defined by time-varying parameters, nonlinear behaviors, and uncertainties. These characteristics require sophistica…
Generative Multimodal Multiscale Data Fusion for Digital Twins in Aerosol Jet Electronics Printing
Fatemeh Elhambakhsh, Suk Ki Lee, Hyunwoong Ko
The rising demand for high-value electronics necessitates advanced manufacturing techniques capable of meeting stringent specifications for precise, complex, and compact devices, d…