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Advanced Process Monitoring for Industry 4.0

This book reports recent advances on Process Monitoring (PM) to cope with the many challenges raised by the new production systems, sensors and "extreme data" conditions that emerged with Industry 4.0. Concepts such as digital-twins and deep learning are brought to the PM arena, pushing fo...

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Bibliographic Details
Main Author: Reis, Marco S.
Other Authors: Gao, Furong
Format: eBook
Language:English
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
Quality Control
Process Monitoring
Risk Priority Number
Data Mining
Optical Sensors
Industry 4.0
Signal Detection
Condition Monitoring
Rolling Bearing
N/a
Data Reconciliation
Data Augmentation
Multiscale
Latent Variables Models
Monitoring
Pasting Process
Digital Processing
Auto Machine Learning
Neural Networks
Online
Process Image
Pca
Spatial-temporal Data
Disruption Management
Six Sigma
Fault Detection
Technology: General Issues / Bicssc
Decision Support Systems
Plaster Production
Imbalanced Data
High-dimensional Data
Curve Resolution
Multivariate Data Analysis
Failure Mode And Effects Analysis (fmea)
Pls
Principal Component Analysis
Non-intrusive Load Monitoring
Continuous Casting
Semiconductor Manufacturing
Real-time
Optics
Process Control
Statistical Process Monitoring
Time Series Classification
Yield Improvement
Expert Systems
Spectroscopy Measurements
Discriminant Analysis
Fault Diagnosis
Control Chart Pattern
Statistical Process Control
Combustion
Failure Mode Effects Analysis
Artificial Generation Of Variability
Disruptions
Quality Prediction
Membrane
Classification
Multi-phase Residual Recursive Model
Construction Industry
Multi-mode Model
Convolutional Neural Network
Load Identification
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:This book reports recent advances on Process Monitoring (PM) to cope with the many challenges raised by the new production systems, sensors and "extreme data" conditions that emerged with Industry 4.0. Concepts such as digital-twins and deep learning are brought to the PM arena, pushing forward the capabilities of existing methodologies to handle more complex scenarios. The evolution of classical paradigms such as Latent Variable modeling, Six Sigma and FMEA are also covered. Applications span a wide range of domains such as microelectronics, semiconductors, chemicals, materials, agriculture, as well as the monitoring of rotating equipment, combustion systems and membrane separation processes.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (288 p.)
ISBN:books978-3-0365-2074-2
9783036520742
9783036520735

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