Challenges of modeling and analysis in cybermanufacturing: a review from a machine learning and computation perspective

SK Kang, R **, X Deng, RS Kenett - Journal of Intelligent Manufacturing, 2023 - Springer
Abstract In Industry 4.0, smart manufacturing is facing its next stage, cybermanufacturing,
founded upon advanced communication, computation, and control infrastructure …

In-process quality improvement: Concepts, methodologies, and applications

J Shi - IISE transactions, 2023 - Taylor & Francis
This article presents the concepts, methodologies, and applications of In-Process Quality
Improvement (IPQI) in complex manufacturing systems. As opposed to traditional quality …

Inn: An interpretable neural network for ai incubation in manufacturing

X Chen, Y Zeng, S Kang, R ** - ACM Transactions on Intelligent …, 2022 - dl.acm.org
Both artificial intelligence (AI) and domain knowledge from human experts play an important
role in manufacturing decision making. Smart manufacturing emphasizes a fully automated …

Functional quantitative and qualitative models for quality modeling in a fused deposition modeling process

H Sun, PK Rao, ZJ Kong, X Deng… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Additive manufacturing (AM) enables flexible part geometry and functionality, and reduces
product development life cycle by direct layer-wise fabrication from CAD files. In the last …

Quality modeling of printed electronics in aerosol jet printing based on microscopic images

H Sun, K Wang, Y Li, C Zhang… - Journal of …, 2017 - asmedigitalcollection.asme.org
Aerosol jet printing (AJP) is a direct write technology that enables fabrication of flexible, fine
scale printed electronics on conformal substrates. AJP does not require the time consuming …

Net-zero energy factory: Exploitation of flexibility–A technical-economic analysis for a German carpentry

P Lombardi, M Liserre - 2022 IEEE 21st Mediterranean …, 2022 - ieeexplore.ieee.org
Industrial facilities hide a high potential of flexibility, whose exploitation might contribute to
accelerating the decarbonization process. This study deals with the identification …

Logistic regression for crystal growth process modeling through hierarchical nonnegative garrote-based variable selection

H Sun, X Deng, K Wang, R ** - Iie Transactions, 2016 - Taylor & Francis
Single-crystal silicon ingots are produced from a complex crystal growth process. Such a
process is sensitive to subtle process condition changes, which may easily become failed …

Functional graphical models for manufacturing process modeling

H Sun, S Huang, R ** - IEEE Transactions on Automation …, 2017 - ieeexplore.ieee.org
Graphical models are widely used to model the statistical relationships among variables in a
system. Existing graphical models can be used to model the relationships among scalar …

A Bayesian hierarchical model for quantitative and qualitative responses

L Kang, X Kang, X Deng, R ** - Journal of Quality Technology, 2018 - Taylor & Francis
In many science and engineering systems both quantitative and qualitative output
observations are collected. If modeled separately the important relationship between the two …

Bayesian sparse regression for mixed multi-responses with application to runtime metrics prediction in fog manufacturing

X Chen, X Kang, R **, X Deng - Technometrics, 2023 - Taylor & Francis
Fog manufacturing can greatly enhance traditional manufacturing systems through
distributed Fog computation units, which are governed by predictive computational workload …