Marian M, Tremmel S (2021)
Publication Language: English
Publication Type: Journal article, Review article
Publication year: 2021
Book Volume: 9
Pages Range: 1-30
Article Number: 86
Journal Issue: 9
URI: https://www.mdpi.com/2075-4442/9/9/86
DOI: 10.3390/lubricants9090086
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.
APA:
Marian, M., & Tremmel, S. (2021). Current Trends and Applications of Machine Learning in Tribology—A Review. Lubricants, 9(9), 1-30. https://doi.org/10.3390/lubricants9090086
MLA:
Marian, Max, and Stephan Tremmel. "Current Trends and Applications of Machine Learning in Tribology—A Review." Lubricants 9.9 (2021): 1-30.
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