IIoT/IoT and Artificial Intelligence/Machine Learning as a Process Optimization Driver under Industry 4.0 Model

The advance of digitalization in industry is making possible that connected products and processes help people, industrial plants and equipment to be more productive and efficient, and the results for operative processes should impact throughout the economy and the environment. Connected products a...

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Detalles Bibliográficos
Autores principales: Walas Mateo, Federico, Redchuk, Andrés
Formato: Articulo
Lenguaje:Inglés
Publicado: 2021
Materias:
Ciencias Informáticas
Artificial intelligence
IIoT
IoT
Machine learning
Industry 4.0
Inteligencia artificial
Aprendizaje Automático
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/128267
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-128267
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Artificial intelligence
IIoT
IoT
Machine learning
Industry 4.0
Inteligencia artificial
Aprendizaje Automático
spellingShingle Ciencias Informáticas
Artificial intelligence
IIoT
IoT
Machine learning
Industry 4.0
Inteligencia artificial
Aprendizaje Automático
Walas Mateo, Federico
Redchuk, Andrés
IIoT/IoT and Artificial Intelligence/Machine Learning as a Process Optimization Driver under Industry 4.0 Model
topic_facet Ciencias Informáticas
Artificial intelligence
IIoT
IoT
Machine learning
Industry 4.0
Inteligencia artificial
Aprendizaje Automático
description The advance of digitalization in industry is making possible that connected products and processes help people, industrial plants and equipment to be more productive and efficient, and the results for operative processes should impact throughout the economy and the environment. Connected products and processes generate data that is being seen as a key source of competitive advantage, and the management and processing of that data is generating new challenges in the industrial environment. The article to be presented looks into the framework of the adoption of Artificial Intelligence and Machine Learning and its integration with IIoT (industrial Internet of Things) or IoT (Internet of Things) under industry 4.0, or smart manufacturing framework. This work is focused on the discussion around Artificial Intelligence/Machine Learning and IIoT/IoT as driver for Industrial Process optimization. The paper explore some related articles that were find relevant to start the discussion, and includes a bibliometric analysis of the key topics around Artificial Intelligence/Machine Learning as a value added solution for process optimization under Industry 4.0 or Smart Manufacturing paradigm. The main findings are related to the importance that the subject has acquired since 2013 in terms of published articles, and the complexity of the approach of the issue proposed by this work in the industrial environment.
format Articulo
Articulo
author Walas Mateo, Federico
Redchuk, Andrés
author_facet Walas Mateo, Federico
Redchuk, Andrés
author_sort Walas Mateo, Federico
title IIoT/IoT and Artificial Intelligence/Machine Learning as a Process Optimization Driver under Industry 4.0 Model
title_short IIoT/IoT and Artificial Intelligence/Machine Learning as a Process Optimization Driver under Industry 4.0 Model
title_full IIoT/IoT and Artificial Intelligence/Machine Learning as a Process Optimization Driver under Industry 4.0 Model
title_fullStr IIoT/IoT and Artificial Intelligence/Machine Learning as a Process Optimization Driver under Industry 4.0 Model
title_full_unstemmed IIoT/IoT and Artificial Intelligence/Machine Learning as a Process Optimization Driver under Industry 4.0 Model
title_sort iiot/iot and artificial intelligence/machine learning as a process optimization driver under industry 4.0 model
publishDate 2021
url http://sedici.unlp.edu.ar/handle/10915/128267
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AT redchukandres iiotiotandartificialintelligencemachinelearningasaprocessoptimizationdriverunderindustry40model
AT walasmateofederico iiotioteinteligenciaartificialaprendizajeautomaticocomomotordeoptimizaciondeprocesosenelmodelodeindustria40
AT redchukandres iiotioteinteligenciaartificialaprendizajeautomaticocomomotordeoptimizaciondeprocesosenelmodelodeindustria40
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