Advanced Process Monitoring for Industry 4.0

• Other Authors: Reis, Marco S. (Editor), Gao, Furong (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Subjects: Technology: general issues; spatial-temporal data; pasting process; process image; convolutional neural network; Industry 4.0; auto machine learning; failure mode effects analysis; risk priority number; rolling bearing; condition monitoring; classification; OPTICS; statistical process control; control chart pattern; disruptions; disruption management; fault diagnosis; construction industry; plaster production; neural networks; decision support systems; expert systems; failure mode and effects analysis (FMEA); discriminant analysis; non-intrusive load monitoring; load identification; membrane; data reconciliation; real-time; online; monitoring; Six Sigma; multivariate data analysis; latent variables models; PCA; PLS; high-dimensional data; statistical process monitoring; artificial generation of variability; data augmentation; quality prediction; continuous casting; multiscale; time series classification; imbalanced data; combustion; optical sensors; spectroscopy measurements; signal detection; digital processing; principal component analysis; curve resolution; data mining; semiconductor manufacturing; quality control; yield improvement; fault detection; process control; multi-phase residual recursive model; multi-mode model; process monitoring; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

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...