A machine learning-based workflow for automatic detection of anomalies in machine tools-Reference-Cited by-同舟云学术

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A machine learning-based workflow for automatic detection of anomalies in machine tools

Published:2021-07 Issue: Volume: Page:
ISSN:0019-0578
Container-title:ISA Transactions
language:en
Short-container-title:ISA Transactions

Author:

Züfle Marwin^ORCID,Moog Felix,Lesch Veronika^ORCID,Krupitzer Christian^ORCID,Kounev Samuel^ORCID

Funder

Deutsche Forschungsgemeinschaft

Publisher

Elsevier BV

Subject

Applied Mathematics,Control and Systems Engineering,Electrical and Electronic Engineering,Computer Science Applications,Instrumentation

Reference36 articles.

1. Guest editorial industry 4.0–prerequisites and visions;Vogel-Heuser;IEEE Trans Autom Sci Eng,2016

2. Simply collecting data is not enough;Bosch Rexroth,2020

3. Industrial Internet of Things: Unleashing the potential of connected products and services;World Economic Forum,2015

4. An introduction to predictive maintenance;Mobley,2002

5. A survey on predictive maintenance for industry 4.0;Krupitzer,2020

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2. A systematic multi-layer cognitive model for intelligent machine tool;Journal of Intelligent Manufacturing;2024-08-30

3. Detección de anomalías en máquinas de corte con láser mediante redes neuronales y procesamiento de señales;Jornadas de Automática;2024-07-16

4. A MOGA and extended RPN based approach for heuristic key reliability characteristics analysis in manufacturing;ISA Transactions;2024-07

5. Predictive maintenance in Industry 4.0: A systematic multi-sector mapping;CIRP Journal of Manufacturing Science and Technology;2024-06

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