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

Marian M, Tremmel S (2021)

Publication Language: English

Publication Type: Journal article, Review article

Publication year: 2021

Journal

Lubricants MDPI

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

Abstract

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.

Authors with CRIS profile

Max Marian Chair of Engineering Design

Involved external institutions

Universität Bayreuth DE Germany (DE)

How to cite

APA:

Marian, M., & Tremmel, S. (2021). Current Trends and Applications of Machine Learning in Tribology—A Review. Lubricants, 9(9), 1-30. https://dx.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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