New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes

Modern factories are experiencing rapid digital transformation supported by emerging technologies, such as the Industrial Internet of things (IIOT), industrial big data and cloud technologies, deep learning and deep analytics, AI, intelligent robotics, cyber-physical systems and digital twins, compl...

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Main Authors: Posada, Jorge, López de Lacalle, Luis Norberto
Formato: Online
Idioma:inglês
Publicado em: MDPI - Multidisciplinary Digital Publishing Institute 2021
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AHP
FCM
LGM
QFD
HED
BIM
Acesso em linha:44832
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author Posada, Jorge
López de Lacalle, Luis Norberto
author_browse López de Lacalle, Luis Norberto
Posada, Jorge
author_facet Posada, Jorge
López de Lacalle, Luis Norberto
author_sort Posada, Jorge
collection Directory of Open Access Books
description Modern factories are experiencing rapid digital transformation supported by emerging technologies, such as the Industrial Internet of things (IIOT), industrial big data and cloud technologies, deep learning and deep analytics, AI, intelligent robotics, cyber-physical systems and digital twins, complemented by visual computing (including new forms of artificial vision with machine learning, novel HMI, simulation, and visualization). This is evident in the global trend of Industry 4.0. The impact of these technologies is clear in the context of high-performance manufacturing. Important improvements can be achieved in productivity, systems reliability, quality verification, etc. Manufacturing processes, based on advanced mechanical principles, are enhanced by big data analytics on industrial sensor data. In current machine tools and systems, complex sensors gather useful data, which is captured, stored, and processed with edge, fog, or cloud computing. These processes improve with digital monitoring, visual data analytics, AI, and computer vision to achieve a more productive and reliable smart factory. New value chains are also emerging from these technological changes. This book addresses these topics, including contributions deployed in production, as well as general aspects of Industry 4.0.
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publisherStr MDPI - Multidisciplinary Digital Publishing Institute
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spelling doab-20.500.12854ir-545832024-04-11T15:10:26Z New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes Posada, Jorge López de Lacalle, Luis Norberto TA1-2040 T55.4-60.8 T1-995 localization smart system n/a connected enterprise digital manufacturing AHP YOLOv3 decision support neural network vertex distance depthwise separable convolution cutting insert selection smart service contour detection convolutional neural networks platform-based ecosystem in-line dimensional inspection dilated convolutions fabric defect detection classification FCM LGM digital information flow turning computer vision control service blister defect RMTs feature pyramid research and development indicators maintenance expert polymer lithium-ion battery IT concept Industry 4.0 matching data reduction competence fibre of preserved Szechuan pickle elliptical paraboloid array relative angle geometric relationship optical system configure-to-order aircraft structure crack detection digital twins smart factory D-VGG16 optical slope sensor smart manufacturing self-calibration method convolutional neural network industry 4.0 skyline queries machine learning scalability test cyber-physical production systems Cyber-Physical Systems (CPS) demand-side response cutting parameter optimization image smoothing marketing innovations genetic algorithm automation system defect detection scheduling job shop systems big data operator theory micro-armature train wheel industrial knowledge graph industrial load management bilinear model artificial neural networks 4th industrial revolution INDUSTRY 4.0 construction equipment lean assembly capacity control Grad-CAM revolution workpiece chatter anomaly detection QFD social network deep learning control as a service warm forming automated surface inspection cloud-based control system innovative marketing tools Internet of Things (IoT) flower pollination algorithm HED edge computing predictive analytics BIM digital platforms industrial big data energy flexibility impacts marketing innovations intellectualization of industrial information economic recession 3D mesh reconstruction demand-side management thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Modern factories are experiencing rapid digital transformation supported by emerging technologies, such as the Industrial Internet of things (IIOT), industrial big data and cloud technologies, deep learning and deep analytics, AI, intelligent robotics, cyber-physical systems and digital twins, complemented by visual computing (including new forms of artificial vision with machine learning, novel HMI, simulation, and visualization). This is evident in the global trend of Industry 4.0. The impact of these technologies is clear in the context of high-performance manufacturing. Important improvements can be achieved in productivity, systems reliability, quality verification, etc. Manufacturing processes, based on advanced mechanical principles, are enhanced by big data analytics on industrial sensor data. In current machine tools and systems, complex sensors gather useful data, which is captured, stored, and processed with edge, fog, or cloud computing. These processes improve with digital monitoring, visual data analytics, AI, and computer vision to achieve a more productive and reliable smart factory. New value chains are also emerging from these technological changes. This book addresses these topics, including contributions deployed in production, as well as general aspects of Industry 4.0. 2021-02-11T20:54:47Z 2021-02-11T20:54:47Z 2020-04-07 23:07:09 2020 book 44832 9783039282906 9783039282913 https://directory.doabooks.org/handle/20.500.12854/54583 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/2109 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03928-291-3 10.3390/books978-3-03928-291-3 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039282906 9783039282913 428 open access
spellingShingle TA1-2040
T55.4-60.8
T1-995
localization
smart system
n/a
connected enterprise
digital manufacturing
AHP
YOLOv3
decision support
neural network
vertex distance
depthwise separable convolution
cutting insert selection
smart service
contour detection
convolutional neural networks
platform-based ecosystem
in-line dimensional inspection
dilated convolutions
fabric defect detection
classification
FCM
LGM
digital information flow
turning
computer vision
control service
blister defect
RMTs
feature pyramid
research and development indicators
maintenance expert
polymer lithium-ion battery
IT concept
Industry 4.0
matching
data reduction
competence
fibre of preserved Szechuan pickle
elliptical paraboloid array
relative angle
geometric relationship
optical system
configure-to-order
aircraft structure crack detection
digital twins
smart factory
D-VGG16
optical slope sensor
smart manufacturing
self-calibration method
convolutional neural network
industry 4.0
skyline queries
machine learning
scalability test
cyber-physical production systems
Cyber-Physical Systems (CPS)
demand-side response
cutting parameter optimization
image smoothing
marketing innovations
genetic algorithm
automation system
defect detection
scheduling
job shop systems
big data
operator theory
micro-armature
train wheel
industrial knowledge graph
industrial load management
bilinear model
artificial neural networks
4th industrial revolution
INDUSTRY 4.0
construction equipment
lean assembly
capacity control
Grad-CAM
revolution workpiece
chatter
anomaly detection
QFD
social network
deep learning
control as a service
warm forming
automated surface inspection
cloud-based control system
innovative marketing tools
Internet of Things (IoT)
flower pollination algorithm
HED
edge computing
predictive analytics
BIM
digital platforms
industrial big data
energy flexibility
impacts marketing innovations
intellectualization of industrial information
economic recession
3D mesh reconstruction
demand-side management
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Posada, Jorge
López de Lacalle, Luis Norberto
New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes
title New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes
title_full New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes
title_fullStr New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes
title_full_unstemmed New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes
title_short New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes
title_sort new industry 4 0 advances in industrial iot and visual computing for manufacturing processes
topic TA1-2040
T55.4-60.8
T1-995
localization
smart system
n/a
connected enterprise
digital manufacturing
AHP
YOLOv3
decision support
neural network
vertex distance
depthwise separable convolution
cutting insert selection
smart service
contour detection
convolutional neural networks
platform-based ecosystem
in-line dimensional inspection
dilated convolutions
fabric defect detection
classification
FCM
LGM
digital information flow
turning
computer vision
control service
blister defect
RMTs
feature pyramid
research and development indicators
maintenance expert
polymer lithium-ion battery
IT concept
Industry 4.0
matching
data reduction
competence
fibre of preserved Szechuan pickle
elliptical paraboloid array
relative angle
geometric relationship
optical system
configure-to-order
aircraft structure crack detection
digital twins
smart factory
D-VGG16
optical slope sensor
smart manufacturing
self-calibration method
convolutional neural network
industry 4.0
skyline queries
machine learning
scalability test
cyber-physical production systems
Cyber-Physical Systems (CPS)
demand-side response
cutting parameter optimization
image smoothing
marketing innovations
genetic algorithm
automation system
defect detection
scheduling
job shop systems
big data
operator theory
micro-armature
train wheel
industrial knowledge graph
industrial load management
bilinear model
artificial neural networks
4th industrial revolution
INDUSTRY 4.0
construction equipment
lean assembly
capacity control
Grad-CAM
revolution workpiece
chatter
anomaly detection
QFD
social network
deep learning
control as a service
warm forming
automated surface inspection
cloud-based control system
innovative marketing tools
Internet of Things (IoT)
flower pollination algorithm
HED
edge computing
predictive analytics
BIM
digital platforms
industrial big data
energy flexibility
impacts marketing innovations
intellectualization of industrial information
economic recession
3D mesh reconstruction
demand-side management
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
topic_facet TA1-2040
T55.4-60.8
T1-995
localization
smart system
n/a
connected enterprise
digital manufacturing
AHP
YOLOv3
decision support
neural network
vertex distance
depthwise separable convolution
cutting insert selection
smart service
contour detection
convolutional neural networks
platform-based ecosystem
in-line dimensional inspection
dilated convolutions
fabric defect detection
classification
FCM
LGM
digital information flow
turning
computer vision
control service
blister defect
RMTs
feature pyramid
research and development indicators
maintenance expert
polymer lithium-ion battery
IT concept
Industry 4.0
matching
data reduction
competence
fibre of preserved Szechuan pickle
elliptical paraboloid array
relative angle
geometric relationship
optical system
configure-to-order
aircraft structure crack detection
digital twins
smart factory
D-VGG16
optical slope sensor
smart manufacturing
self-calibration method
convolutional neural network
industry 4.0
skyline queries
machine learning
scalability test
cyber-physical production systems
Cyber-Physical Systems (CPS)
demand-side response
cutting parameter optimization
image smoothing
marketing innovations
genetic algorithm
automation system
defect detection
scheduling
job shop systems
big data
operator theory
micro-armature
train wheel
industrial knowledge graph
industrial load management
bilinear model
artificial neural networks
4th industrial revolution
INDUSTRY 4.0
construction equipment
lean assembly
capacity control
Grad-CAM
revolution workpiece
chatter
anomaly detection
QFD
social network
deep learning
control as a service
warm forming
automated surface inspection
cloud-based control system
innovative marketing tools
Internet of Things (IoT)
flower pollination algorithm
HED
edge computing
predictive analytics
BIM
digital platforms
industrial big data
energy flexibility
impacts marketing innovations
intellectualization of industrial information
economic recession
3D mesh reconstruction
demand-side management
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
url 44832
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