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Artificial Intelligence and Machine Learning Applications in Smart Production: Progress, Trends, and Directions

1
Department of Engineering, Parthenope University, Isola C4, Centro Direzionale, 80143 Napoli NA, Italy
2
Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Via G. Di Biasio, 43, 03043 Cassino FR, Italy
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(2), 492; https://doi.org/10.3390/su12020492
Received: 1 December 2019 / Revised: 3 January 2020 / Accepted: 5 January 2020 / Published: 8 January 2020
(This article belongs to the Collection Smart Production Operations Management and Industry 4.0)
Adaptation and innovation are extremely important to the manufacturing industry. This development should lead to sustainable manufacturing using new technologies. To promote sustainability, smart production requires global perspectives of smart production application technology. In this regard, thanks to intensive research efforts in the field of artificial intelligence (AI), a number of AI-based techniques, such as machine learning, have already been established in the industry to achieve sustainable manufacturing. Thus, the aim of the present research was to analyze, systematically, the scientific literature relating to the application of artificial intelligence and machine learning (ML) in industry. In fact, with the introduction of the Industry 4.0, artificial intelligence and machine learning are considered the driving force of smart factory revolution. The purpose of this review was to classify the literature, including publication year, authors, scientific sector, country, institution, and keywords. The analysis was done using the Web of Science and SCOPUS database. Furthermore, UCINET and NVivo 12 software were used to complete them. A literature review on ML and AI empirical studies published in the last century was carried out to highlight the evolution of the topic before and after Industry 4.0 introduction, from 1999 to now. Eighty-two articles were reviewed and classified. A first interesting result is the greater number of works published by the USA and the increasing interest after the birth of Industry 4.0. View Full-Text
Keywords: artificial intelligence; machine learning; systematic literature review; applications; Industry 4.0; smart production; sustainability artificial intelligence; machine learning; systematic literature review; applications; Industry 4.0; smart production; sustainability
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MDPI and ACS Style

Cioffi, R.; Travaglioni, M.; Piscitelli, G.; Petrillo, A.; De Felice, F. Artificial Intelligence and Machine Learning Applications in Smart Production: Progress, Trends, and Directions. Sustainability 2020, 12, 492. https://doi.org/10.3390/su12020492

AMA Style

Cioffi R, Travaglioni M, Piscitelli G, Petrillo A, De Felice F. Artificial Intelligence and Machine Learning Applications in Smart Production: Progress, Trends, and Directions. Sustainability. 2020; 12(2):492. https://doi.org/10.3390/su12020492

Chicago/Turabian Style

Cioffi, Raffaele; Travaglioni, Marta; Piscitelli, Giuseppina; Petrillo, Antonella; De Felice, Fabio. 2020. "Artificial Intelligence and Machine Learning Applications in Smart Production: Progress, Trends, and Directions" Sustainability 12, no. 2: 492. https://doi.org/10.3390/su12020492

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