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Challenges of modeling and analysis in cybermanufacturing: a review from a machine learning and computation perspective
Abstract In Industry 4.0, smart manufacturing is facing its next stage, cybermanufacturing,
founded upon advanced communication, computation, and control infrastructure …
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 …
Improvement (IPQI) in complex manufacturing systems. As opposed to traditional quality …
Inn: An interpretable neural network for ai incubation in manufacturing
Both artificial intelligence (AI) and domain knowledge from human experts play an important
role in manufacturing decision making. Smart manufacturing emphasizes a fully automated …
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
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 …
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
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 …
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 …
accelerating the decarbonization process. This study deals with the identification …
Logistic regression for crystal growth process modeling through hierarchical nonnegative garrote-based variable selection
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 …
process is sensitive to subtle process condition changes, which may easily become failed …
Functional graphical models for manufacturing process modeling
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 …
system. Existing graphical models can be used to model the relationships among scalar …
A Bayesian hierarchical model for quantitative and qualitative responses
In many science and engineering systems both quantitative and qualitative output
observations are collected. If modeled separately the important relationship between the two …
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
Fog manufacturing can greatly enhance traditional manufacturing systems through
distributed Fog computation units, which are governed by predictive computational workload …
distributed Fog computation units, which are governed by predictive computational workload …