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Machine Learning in Industry 4.0: a systematic review

By
Luis Stalin López Telenchana ,
Luis Stalin López Telenchana

Universidad Nacional de Chimborazo, Ingeniería Industrial. Chimborazo, Ecuador

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Gabriela Joseth Serrano Torres ,
Gabriela Joseth Serrano Torres

Universidad Nacional de Chimborazo, Ingeniería Industrial. Chimborazo, Ecuador

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Ximena Alexandra Quintana López ,
Ximena Alexandra Quintana López

Universidad Nacional de Chimborazo, Ingeniería Industrial. Chimborazo, Ecuador

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Diego Marcelo Reina Haro ,
Diego Marcelo Reina Haro

Universidad Nacional de Chimborazo, Ingeniería Industrial. Chimborazo, Ecuador

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Abstract

The purpose of this article is to expose the processes of automatic learning or Machine Learning in Industry 4.0 based on a systematic review that allows the search for studies and research on the use of innovation technologies. To that extent, the proposed objective is developed through a mixed approach, that is, it integrates both a quantitative proposal regarding previous studies on the subject and also, consolidating a qualitative analysis that critically determines the effectiveness of machine learning in the development industrial and commercial, performance and well-being. In this way, the search is carried out in academic databases such as Scopus, Scielo, Dialnet and Redalyc so that research studies or degree works that propose appropriate implementation strategies and help to consolidate a discussion about the machine are linked. Learning in the fourth industrial revolution.

How to Cite

1.
López Telenchana LSL, Serrano Torres GJ, Quintana López XA, Reina Haro DM. Machine Learning in Industry 4.0: a systematic review. Salud, Ciencia y Tecnología [Internet]. 2024 May 28 [cited 2024 Jun. 20];4:1068. Available from: https://revista.saludcyt.ar/ojs/index.php/sct/article/view/1068

The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.

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