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Review

Current Trends and Applications of Machine Learning in Tribology—A Review

1
Engineering Design, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Martensstr. 9, 91058 Erlangen, Germany
2
Engineering Design and CAD, University of Bayreuth, Universitätsstr. 30, 95477 Bayreuth, Germany
*
Author to whom correspondence should be addressed.
Lubricants 2021, 9(9), 86; https://doi.org/10.3390/lubricants9090086
Received: 27 July 2021 / Revised: 22 August 2021 / Accepted: 25 August 2021 / Published: 1 September 2021
(This article belongs to the Special Issue Machine Learning in Tribology)
Machine learning (ML) and artificial intelligence (AI) are rising stars in many scientific disciplines and industries, and high hopes are being pinned upon them. Likewise, ML and AI approaches have also found their way into tribology, where they can support sorting through the complexity of patterns and identifying trends within the multiple interacting features and processes. Published research extends across many fields of tribology from composite materials and drive technology to manufacturing, surface engineering, and lubricants. Accordingly, the intended usages and numerical algorithms are manifold, ranging from artificial neural networks (ANN), decision trees over random forest and rule-based learners to support vector machines. Therefore, this review is aimed to introduce and discuss the current trends and applications of ML and AI in tribology. Thus, researchers and R&D engineers shall be inspired and supported in the identification and selection of suitable and promising ML approaches and strategies. View Full-Text
Keywords: tribology; machine learning; artificial intelligence; triboinformatics; databases; data mining; meta-modeling; artificial neural networks; monitoring; analysis; prediction; optimization tribology; machine learning; artificial intelligence; triboinformatics; databases; data mining; meta-modeling; artificial neural networks; monitoring; analysis; prediction; optimization
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MDPI and ACS Style

Marian, M.; Tremmel, S. Current Trends and Applications of Machine Learning in Tribology—A Review. Lubricants 2021, 9, 86. https://doi.org/10.3390/lubricants9090086

AMA Style

Marian M, Tremmel S. Current Trends and Applications of Machine Learning in Tribology—A Review. Lubricants. 2021; 9(9):86. https://doi.org/10.3390/lubricants9090086

Chicago/Turabian Style

Marian, Max, and Stephan Tremmel. 2021. "Current Trends and Applications of Machine Learning in Tribology—A Review" Lubricants 9, no. 9: 86. https://doi.org/10.3390/lubricants9090086

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