Rosenkranz A, Marian M, Profito FJ, Aragon N, Shah R (2021)
Publication Language: English
Publication Type: Journal article, other
Publication year: 2021
Book Volume: 9
Pages Range: 1-11
Article Number: 2
Journal Issue: 1
URI: https://www.mdpi.com/2075-4442/9/1/2
DOI: 10.3390/lubricants9010002
Open Access Link: https://www.mdpi.com/2075-4442/9/1/2
Artificial intelligence and, in particular, machine learning methods have gained notable attention in the tribological community due to their ability to predict tribologically relevant parameters such as, for instance, the coefficient of friction or the oil film thickness. This perspective aims at highlighting some of the recent advances achieved by implementing artificial intelligence, specifically artificial neutral networks, towards tribological research. The presentation and discussion of successful case studies using these approaches in a tribological context clearly demonstrates their ability to accurately and efficiently predict these tribological characteristics. Regarding future research directions and trends, we emphasis on the extended use of artificial intelligence and machine learning concepts in the field of tribology including the characterization of the resulting surface topography and the design of lubricated systems.
APA:
Rosenkranz, A., Marian, M., Profito, F.J., Aragon, N., & Shah, R. (2021). The Use of Artificial Intelligence in Tribology - A Perspective. Lubricants, 9(1), 1-11. https://dx.doi.org/10.3390/lubricants9010002
MLA:
Rosenkranz, Andreas, et al. "The Use of Artificial Intelligence in Tribology - A Perspective." Lubricants 9.1 (2021): 1-11.
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