Works (28)

Updated: November 25th, 2024 21:30

2024 journal article

A distributionally robust chance-constrained kernel-free quadratic surface support vector machine

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 316(1), 46–60.

By: F. Lin n, S. Fang n, X. Fang n, Z. Gao* & J. Luo*

author keywords: Data science; Kernel-free support vector machine; Robust classification; Distributionally robust optimization; Chance-constrained optimization
Sources: Web Of Science, NC State University Libraries, ORCID
Added: May 7, 2024

2024 article

A federated data fusion-based prognostic model for applications with multi-stream incomplete signals

Arabi, M., & Fang, X. (2024, June 10). IISE TRANSACTIONS, Vol. 6.

By: M. Arabi n & X. Fang n

author keywords: Federated learning; federated data fusion; remaining useful life
Sources: Web Of Science, NC State University Libraries
Added: July 17, 2024

2024 journal article

Distributionally robust chance-constrained kernel-based support vector machine

COMPUTERS & OPERATIONS RESEARCH, 170.

By: F. Lin*, S. Fang*, X. Fang* & Z. Gao

author keywords: Uncertainty; Support vector machine; Distributionally robust optimization; Data-driven approach; ADMM
Sources: Web Of Science, NC State University Libraries
Added: July 30, 2024

2024 journal article

Machine identity authentication via unobservable fingerprinting signature: A functional data analysis approach for MQTT 5.0 protocol

JOURNAL OF MANUFACTURING SYSTEMS, 76, 59–74.

By: P. Koprov*, X. Fang* & B. Starly*

author keywords: Functional data analysis; Machine identity authentication; MQTT Security; Industrial internet of things; Smart manufacturing; Industrial cybersecurity
Sources: Web Of Science, NC State University Libraries
Added: August 14, 2024

2024 article

Tensor-based statistical learning methods for diagnosing product quality defects in multistage manufacturing processes

Jeong, C., Byon, E., He, F., & Fang, X. (2024, August 9). IISE TRANSACTIONS, Vol. 8.

By: C. Jeong*, E. Byon*, F. He* & X. Fang n

author keywords: Quality defect/fault diagnosis; penalized tensor regression; two-dimensional variable selection
Sources: Web Of Science, NC State University Libraries
Added: September 23, 2024

2023 journal article

Sparse Hierarchical Parallel Residual Networks Ensemble for Infrared Image Stream-Based Remaining Useful Life Prediction

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 19(10), 10613–10623.

author keywords: Degradation; Feature extraction; Streaming media; Residual neural networks; Ensemble learning; Computer architecture; Kernel; Hierarchical parallel residual network (HPRN); infrared image stream-based prognostics; remaining useful life (RUL) prediction; sparse ensemble
TL;DR: A sparse hierarchical parallel residual networks ensemble (SHPRNE) method that leverages parallel multiscale kernels to capture complementary degradation patterns separately and embeds a hierarchical residual connection procedure to facilitate the interactivity between coarse-to-fine level features. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: September 11, 2023

2023 journal article

Systems and methods for authenticating manufacturing Machines through an unobservable fingerprinting system

Manufacturing Letters, 35, 1009–1018.

By: P. Koprov n, S. Gadhwala n, A. Walimbe n, X. Fang n & B. Starly*

author keywords: Cybersecurity; Connected Manufacturing; Authentication; Physical Unclonable Function; Digital Twin; Vibration
Sources: Web Of Science, NC State University Libraries, Crossref, ORCID
Added: October 16, 2023

2022 journal article

A convex two-dimensional variable selection method for the root-cause diagnostics of product defects

RELIABILITY ENGINEERING & SYSTEM SAFETY, 229.

By: C. Zhou n & X. Fang n

author keywords: Fault/defect diagnostics; Quality control; Penalized matrix regression; Group lasso; Sparsity; Generalized linear model
Sources: Web Of Science, NC State University Libraries
Added: November 7, 2022

2022 journal article

Adversarial Regressive Domain Adaptation Approach for Infrared Thermography-Based Unsupervised Remaining Useful Life Prediction

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 18(10), 7219–7229.

author keywords: Feature extraction; Degradation; Task analysis; Convolutional neural networks; Optimization; Reliability; Training; Adversarial learning; deep transfer learning; infrared thermography; regressive domain adaptation (DA); remaining useful life (RUL) prediction
TL;DR: An adversarial regressive domain adaptation (ARDA) approach is put forward to address the challenge of simultaneously aligning marginal and conditional distributions in cross-domain remaining useful life (RUL) prediction. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: September 6, 2022

2022 journal article

Spatiotemporal denoising wavelet network for infrared thermography-based machine prognostics integrating ensemble uncertainty

MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 173.

author keywords: Infrared thermography; Remaining useful life prediction; 4D wavelet convolution layer; Feature denoising; Predictive uncertainty
Sources: Web Of Science, NC State University Libraries
Added: May 31, 2022

2021 review

DISTRIBUTIONALLY ROBUST OPTIMIZATION: A REVIEW ON THEORY AND APPLICATIONS

[Review of ]. NUMERICAL ALGEBRA CONTROL AND OPTIMIZATION, 12(1), 159–212.

By: F. Lin*, X. Fang* & Z. Gao

Contributors: F. Lin*, X. Fang* & Z. Gao

author keywords: Distributionally robust optimization; uncertain decision-making; tractable methods; machine learning; operations research
TL;DR: This paper starts with reviewing the modeling power and computational attractiveness of DRO approaches, induced by the ambiguity sets structure and tractable robust counterpart reformulations, and summarizes the efficient solution methods, out-of-sample performance guarantee, and convergence analysis. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: November 29, 2021

2021 journal article

Infrared image stream based regressors for contactless machine prognostics

MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 154.

By: Y. Dong*, T. Xia*, D. Wang*, X. Fang n & L. Xi*

Contributors: Y. Dong*, T. Xia*, D. Wang*, X. Fang n & L. Xi*

author keywords: Prognostics and health management; Remaining useful life prediction; Neural network; Multiple weighted time window; Image stream based regressor
TL;DR: Images stream based regressors consisting of a neural network and multiple weighted time window policy can predict RUL based on image stream well and MWTW policy has a significant effect on the increase of the prediction accuracy. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: March 8, 2021

2021 journal article

Integrated Remanufacturing and Opportunistic Maintenance Decision-Making for Leased Batch Production Lines

JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 143(8).

Contributors: T. Xia*, K. Zhang*, B. Sun*, X. Fang n & L. Xi*

author keywords: remanufacturing; opportunistic maintenance; product-service paradigm; batch production; saved leasing profit; plant engineering and maintenance
TL;DR: Numerical examples based on the collected information from a leased batch production line of engine crankshaft demonstrate that this proposed R&OM policy could efficiently achieve saved leasing profit maximization, reduce joint decision complexity, and expand OM theory. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: July 19, 2021

2021 journal article

Multichannel profile-based monitoring method and its application in the basic oxygen furnace steelmaking process

JOURNAL OF MANUFACTURING SYSTEMS, 61, 375–390.

By: Q. Qian*, X. Fang n, J. Xu* & M. Li*

Contributors: Q. Qian*, X. Fang n, J. Xu* & M. Li*

author keywords: Condition monitoring; Functional data analysis; Mahalanobis distance; Support vector data description
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID, NC State University Libraries
Added: November 23, 2021

2021 conference paper

Multistream sensor fusion-based prognostics model for systems under multiple operational conditions

Proceedings of the ASME 2021 16th International Manufacturing Science and Engineering Conference, MSEC 2021, 2.

By: X. Li n & X. Fang n

Contributors: X. Li n & X. Fang n

TL;DR: A prognostic framework for systems that operate under dynamic multiple operational conditions that will first extract the degradation signal from each sensor by removing the jump information resulted from the change of operational conditions, and is validated using a degradation data set of aircraft turbofan engines from NASA repository. (via Semantic Scholar)
Source: ORCID
Added: February 24, 2022

2021 journal article

Two-dimensional variable selection and its applications in the diagnostics of product quality defects

IISE TRANSACTIONS, 54(7), 619–629.

By: C. Jeong n & X. Fang n

Contributors: C. Jeong n & X. Fang n

author keywords: Penalized matrix regression; two-dimensional variable selection; adaptive group LASSO; block coordinate proximal descent
Sources: Web Of Science, ORCID, NC State University Libraries
Added: May 24, 2021

2020 journal article

Multi-sensor prognostics modeling for applications with highly incomplete signals

IISE TRANSACTIONS, 53(5), 597–613.

Contributors: X. Fang n, H. Yan*, N. Gebraeel* & K. Paynabar*

author keywords: RUL; degradation modelling; multi-stream signal fusion; missing data
TL;DR: A prognostics methodology capable of using highly incomplete multi-stream degradation signals to predict the residual useful lifetime of partially degraded systems and two computationally efficient algorithms: subspace detection and signal recovery are proposed. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: September 7, 2020

2020 journal article

Remaining useful life prediction based on a multi-sensor data fusion model

RELIABILITY ENGINEERING & SYSTEM SAFETY, 208.

Contributors: N. Li*, N. Gebraeel*, Y. Lei*, X. Fang n, X. Cai* & T. Yan*

author keywords: Prognostic degradation modeling; Remaining useful life prediction; Big data; Multi-sensor fusion; State-space model
TL;DR: A RUL prediction method based on a multi-sensor data fusion model where the inherent degradation process of the system state is expressed using a state transition function following a Wiener process. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: March 22, 2021

2019 journal article

Online Analytics Framework of Sensor-Driven Prognosis and Opportunistic Maintenance for Mass Customization

JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 141(5).

Contributors: T. Xia*, X. Fang n, N. Gebraeel*, L. Xi* & E. Pan*

author keywords: mass customization; condition monitoring; opportunistic maintenance; degradation signal; product order
TL;DR: A systematic framework that integrates a sensor-driven prognostic method and an opportunistic maintenance policy to efficiently reduce maintenance cost, avoid system breakdown, and ensure product quality can be applied not only in an automobile line but also for a broader range of manufacturing lines in mass customization. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: April 15, 2019

2019 article

Penalized matrix regression for two-dimensional variable selection

ArXiv. http://www.scopus.com/inward/record.url?eid=2-s2.0-85098348719&partnerID=MN8TOARS

By: C. Jeong & X. Fang

Contributors: C. Jeong & X. Fang

Source: ORCID
Added: February 24, 2022

2019 journal article

Prognostic and health management for adaptive manufacturing systems with online sensors and flexible structures

COMPUTERS & INDUSTRIAL ENGINEERING, 133, 57–68.

By: Y. Dong*, T. Xia*, X. Fang n, Z. Zhang* & L. Xi*

Contributors: Y. Dong*, T. Xia*, X. Fang n, Z. Zhang* & L. Xi*

author keywords: Prognostic and health management; Online sensor; Flexible structure; Time-to-failure; Flexible opportunistic window
TL;DR: A Bayesian updating prognostic model using sensor-based degradation information for computing each machine’s TTFs is integrated, with an opportunistic maintenance policy handling flexible system structures for optimizing the maintenance scheduling, which enables the dynamic prognosis updating, the notable cost reduction, and the rapid decision making for adaptive manufacturing systems. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: July 15, 2019

2018 journal article

Image-Based Prognostics Using Penalized Tensor Regression

TECHNOMETRICS, 61(3), 369–384.

By: X. Fang n, K. Paynabar* & N. Gebraeel*

Contributors: X. Fang n, K. Paynabar* & N. Gebraeel*

author keywords: Image streams; (Log)-location-scale distribution; Penalized tensor regression; Residual useful lifetimes
TL;DR: A new methodology to predict and update the residual useful lifetime of a system using a sequence of degradation images that integrates tensor linear algebra with traditional location-scale regression widely used in reliability and prognostics is proposed. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: September 9, 2019

2018 conference paper

Real-Time Predictive Analytics Using Degradation Image Data

Proceedings - Annual Reliability and Maintainability Symposium, 2018-January.

By: X. Fang*, K. Paynabar* & N. Gebraeel*

Contributors: X. Fang*, K. Paynabar* & N. Gebraeel*

TL;DR: This paper proposed a penalized (log)-location-scale regression model that can utilize high dimensional tensors to predict the residual useful lifetime of systems and a numerical algorithm with global convergence property was developed for the model estimation. (via Semantic Scholar)
Source: ORCID
Added: February 24, 2022

2017 article

Image-based prognostics using penalized tensor regression

ArXiv. http://www.scopus.com/inward/record.url?eid=2-s2.0-85092884816&partnerID=MN8TOARS

By: X. Fang, K. Paynabar & N. Gebraeel

Contributors: X. Fang, K. Paynabar & N. Gebraeel

Source: ORCID
Added: February 24, 2022

2017 journal article

Lease-Oriented Opportunistic Maintenance for Multi-Unit Leased Systems under Product- Service Paradigm

Journal of Manufacturing Science and Engineering, Transactions of the ASME, 139(7).

Contributors: T. Xia*, L. Xi*, E. Pan*, X. Fang* & N. Gebraeel*

author keywords: opportunistic maintenance; product-service paradigm; leasing profit optimization; multi-unit leased system; individual machine deterioration
Source: ORCID
Added: February 24, 2022

2016 journal article

Multistream sensor fusion-based prognostics model for systems with single failure modes

Reliability Engineering and System Safety, 159, 322–331.

By: X. Fang*, K. Paynabar* & N. Gebraeel*

Contributors: X. Fang*, K. Paynabar* & N. Gebraeel*

author keywords: Degradation modeling; Functional variables selection; (log)-location-scale regression; Multivariate functional principal components analysis; Signal fusion
TL;DR: A three-step multi-sensor prognostic methodology that utilizes multistream signals to predict residual useful lifetimes of partially degraded systems and validates using simulation study as well as a case study of aircraft turbofan engines available from NASA repository. (via Semantic Scholar)
Source: ORCID
Added: February 24, 2022

2016 journal article

Scalable prognostic models for large-scale condition monitoring applications

IISE Transactions, 49(7), 698–710.

By: X. Fang*, N. Gebraeel* & K. Paynabar*

Contributors: X. Fang*, N. Gebraeel* & K. Paynabar*

author keywords: Degradation modeling; residual useful life; functional (log)-location-scale regression; functional principal components analysis; signal fusion
TL;DR: A scalable semi-parametric statistical framework specifically designed for synthesizing and combining multistream sensor signals using two signal fusion algorithms developed from functional principal component analysis is presented. (via Semantic Scholar)
Source: ORCID
Added: February 24, 2022

2014 journal article

An adaptive functional regression-based prognostic model for applications with missing data

RELIABILITY ENGINEERING & SYSTEM SAFETY, 133, 266–274.

By: X. Fang*, R. Zhou* & N. Gebraeel*

Contributors: X. Fang*, R. Zhou* & N. Gebraeel*

author keywords: Condition monitoring; Prognostics; Functional principal components analysis; Functional regression analysis; Remaining useful life
TL;DR: This paper develops a semi-parametric approach that can be used to predict the remaining lifetime of partially degraded systems and shows that the proposed approach is relatively robust to significant levels of missing data. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: November 7, 2018

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