52 citations · 121 across the 23 of their papers we have counts for
23 papers
Multi-output Extreme Spatial Model for Complex Aircraft Production Systems
Cheolhei Lee, Xing Wang, Xiaowei Yue +1
Problem definition: Data-driven models in machine learning have enabled efficient management of production systems. However, a majority of machine learning models are devoted to mo…
High Dimensional Data Decomposition for Anomaly Detection of Textured Images
Ji Song, Xing Wang, Jianguo Wu +1
In the realm of diverse high-dimensional data, images play a significant role across various processes of manufacturing systems where efficient image anomaly detection has emerged…
R^2-HGP: A Double-Regularized Gaussian Process for Heterogeneous Transfer Learning
Duo Wang, Xinming Wang, Chao Wang +2
Multi-output Gaussian process (MGP) models have attracted significant attention for their flexibility and uncertainty-quantification capabilities, and have been widely adopted in m…
Non-stationary and Sparsely-correlated Multi-output Gaussian Process with Spike-and-Slab Prior
Wang Xinming, Li Yongxiang, Yue Xiaowei +1
Multi-output Gaussian process (MGP) is commonly used as a transfer learning method to leverage information among multiple outputs. A key advantage of MGP is providing uncertainty q…
Advancing Additive Manufacturing through Deep Learning: A Comprehensive Review of Current Progress and Future Challenges
Amirul Islam Saimon, Emmanuel Yangue, Xiaowei Yue +2
This paper presents the first comprehensive literature review of deep learning (DL) applications in additive manufacturing (AM). It addresses the need for a thorough analysis in th…
Sequential Latin Hypercube Design for Two-layer Computer Simulators
Yan Wang, Dianpeng Wang, Xiaowei Yue
The two-layer computer simulators are commonly used to mimic multi-physics phenomena or systems. Usually, the outputs of the first-layer simulator (also called the inner simulator)…
WOOD: Wasserstein-based Out-of-Distribution Detection
Yinan Wang, Wenbo Sun, Jionghua "Judy" Jin +2
The training and test data for deep-neural-network-based classifiers are usually assumed to be sampled from the same distribution. When part of the test samples are drawn from a di…
Nested Bayesian Optimization for Computer Experiments
Yan Wang, Meng Wang, Areej AlBahar +1
Computer experiments can emulate the physical systems, help computational investigations, and yield analytic solutions. They have been widely employed with many engineering applica…
Failure-averse Active Learning for Physics-constrained Systems
Cheolhei Lee, Xing Wang, Jianguo Wu +1
Active learning is a subfield of machine learning that is devised for design and modeling of systems with highly expensive sampling costs. Industrial and engineering systems are ge…
A Robust Asymmetric Kernel Function for Bayesian Optimization, with Application to Image Defect Detection in Manufacturing Systems
Areej AlBahar, Inyoung Kim, Xiaowei Yue
Some response surface functions in complex engineering systems are usually highly nonlinear, unformed, and expensive-to-evaluate. To tackle this challenge, Bayesian optimization, w…
Task Allocation and Coordinated Motion Planning for Autonomous Multi-Robot Optical Inspection Systems
Yinhua Liu, Wenzheng Zhao, Tim Lutz +1
Autonomous multi-robot optical inspection systems are increasingly applied for obtaining inline measurements in process monitoring and quality control. Numerous methods for path pl…
Partitioned Active Learning for Heterogeneous Systems
Cheolhei Lee, Kaiwen Wang, Jianguo Wu +2
Active learning is a subfield of machine learning that focuses on improving the data collection efficiency of expensive-to-evaluate systems. Especially, active learning integrated…
NP-ODE: Neural Process Aided Ordinary Differential Equations for Uncertainty Quantification of Finite Element Analysis
Yinan Wang, Kaiwen Wang, Wenjun Cai +1
Finite element analysis (FEA) has been widely used to generate simulations of complex and nonlinear systems. Despite its strength and accuracy, the limitations of FEA can be summar…
Neural Network Gaussian Process Considering Input Uncertainty for Composite Structures Assembly
Cheolhei Lee, Jianguo Wu, Wenjia Wang +1
Developing machine learning enabled smart manufacturing is promising for composite structures assembly process. To improve production quality and efficiency of the assembly process…
StressNet: Deep Learning to Predict Stress With Fracture Propagation in Brittle Materials
Yinan Wang, Diane Oyen, Weihong +7
Catastrophic failure in brittle materials is often due to the rapid growth and coalescence of cracks aided by high internal stresses. Hence, accurate prediction of maximum internal…
Online Structural Change-point Detection of High-dimensional Streaming Data via Dynamic Sparse Subspace Learning
Ruiyu Xu, Jianguo Wu, Xiaowei Yue +1
High-dimensional streaming data are becoming increasingly ubiquitous in many fields. They often lie in multiple low-dimensional subspaces, and the manifold structures may change ab…
Optimal Path Planning for Automated Dimensional Inspection of Free-Form Surfaces
Yinhua Liu, Wenzheng Zhao, Rui Sun +1
Structural dimensional inspection is vital for the process monitoring, quality control, and fault diagnosis in the mass production of auto bodies. Comparing with the non-contact me…
Tensor decomposition to Compress Convolutional Layers in Deep Learning
Yinan Wang, Weihong "Grace" Guo, Xiaowei Yue
Feature extraction for tensor data serves as an important step in many tasks such as anomaly detection, process monitoring, image classification, and quality control. Although many…
Active Learning for Gaussian Process Considering Uncertainties with Application to Shape Control of Composite Fuselage
Xiaowei Yue, Yuchen Wen, Jeffrey H. Hunt +1
In the machine learning domain, active learning is an iterative data selection algorithm for maximizing information acquisition and improving model performance with limited trainin…
Real-time Data-driven Quality Assessment for Continuous Manufacturing of Carbon Nanotube Buckypaper
Xinran Shi, Xiaowei Yue, Zhiyong Liang +1
Carbon nanotube (CNT) thin sheet, or buckypaper, has shown great potential as a multifunctional platform material due to its desirable properties, including its lightweight nature,…
Gaussian Processes with Input Location Error and Applications to the Composite Parts Assembly Process
Wenjia Wang, Xiaowei Yue, Benjamin Haaland +1
In this paper, we investigate Gaussian process modeling with input location error, where the inputs are corrupted by noise. Here, the best linear unbiased predictor for two cases i…
Effective Model Calibration via Sensible Variable Identification and Adjustment, with Application to Composite Fuselage Simulation
Yan Wang, Xiaowei Yue, Rui Tuo +2
Estimation of model parameters of computer simulators, also known as calibration, is an important topic in many engineering applications. In this paper, we consider the calibration…
Tensor Mixed Effects Model with Applications in Nanomanufacturing Inspection
Xiaowei Yue, Jin Gyu Park, Zhiyong Liang +1
Raman mapping technique has been used to perform in-line quality inspections of nanomanufacturing processes. In such an application, massive high-dimensional Raman mapping data wit…