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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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Bibliographic Details
Main Author: Posada, Jorge
Other Authors: López de Lacalle, Luis Norberto
Format: eBook
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2020
Subjects:
It Concept
Machine Learning
Fabric Defect Detection
Digital Twins
Industry 4.0
3d Mesh Reconstruction
Impacts Marketing Innovations
Predictive Analytics
Fcm
Genetic Algorithm
Scheduling
Industrial Knowledge Graph
Big Data
Ahp
Deep Learning
Localization
Cutting Insert Selection
Cyber-physical Production Systems
Construction Equipment
Platform-based Ecosystem
Control Service
Aircraft Structure Crack Detection
Operator Theory
Dilated Convolutions
Cutting Parameter Optimization
Image Smoothing
4th Industrial Revolution
Polymer Lithium-ion Battery
Yolov3
Automation System
Decision Support
Cyber-physical Systems (cps)
Industrial Big Data
Bilinear Model
Digital Information Flow
Elliptical Paraboloid Array
Optical System
Innovative Marketing Tools
Chatter
Convolutional Neural Networks
Warm Forming
Relative Angle
D-vgg16
Automated Surface Inspection
Computer Vision
Feature Pyramid
Scalability Test
Lgm
Revolution Workpiece
Edge Computing
Internet Of Things (iot)
Vertex Distance
Anomaly Detection
Depthwise Separable Convolution
Demand-side Management
Lean Assembly
Smart Service
Industrial Load Management
Rmts
Micro-armature
Energy Flexibility
Digital Platforms
Fibre Of Preserved Szechuan Pickle
Maintenance Expert
N/a
Optical Slope Sensor
Geometric Relationship
Intellectualization Of Industrial Information
Social Network
Demand-side Response
History Of Engineering And Technology / Bicssc
Flower Pollination Algorithm
In-line Dimensional Inspection
Research And Development Indicators
Turning
Control As A Service
Bim
Cloud-based Control System
Capacity Control
Hed
Connected Enterprise
Marketing Innovations
Train Wheel
Digital Manufacturing
Smart System
Defect Detection
Qfd
Grad-cam
Matching
Configure-to-order
Self-calibration Method
Data Reduction
Smart Manufacturing
Classification
Smart Factory
Economic Recession
Artificial Neural Networks
Skyline Queries
Convolutional Neural Network
Blister Defect
Job Shop Systems
Competence
Neural Network
Contour Detection
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary: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.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by-nc-nd/4.0/
Physical Description:1 electronic resource (428 p.)
ISBN:9783039282906
books978-3-03928-291-3
9783039282913

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