Current Trends and Applications of Machine Learning in Tribology—A Review
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...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-09-01
|
| Series: | Lubricants |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4442/9/9/86 |
| _version_ | 1797518478746320896 |
|---|---|
| author | Max Marian Stephan Tremmel |
| author_facet | Max Marian Stephan Tremmel |
| author_sort | Max Marian |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T07:30:27Z |
| format | Article |
| id | doaj.art-ea0b8e3e8cb346b69d029731fac5f141 |
| institution | Directory Open Access Journal |
| issn | 2075-4442 |
| language | English |
| last_indexed | 2024-03-10T07:30:27Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Lubricants |
| spelling | doaj.art-ea0b8e3e8cb346b69d029731fac5f1412023-11-22T13:57:22ZengMDPI AGLubricants2075-44422021-09-01998610.3390/lubricants9090086Current Trends and Applications of Machine Learning in Tribology—A ReviewMax Marian0Stephan Tremmel1Engineering Design, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Martensstr. 9, 91058 Erlangen, GermanyEngineering Design and CAD, University of Bayreuth, Universitätsstr. 30, 95477 Bayreuth, GermanyMachine 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.https://www.mdpi.com/2075-4442/9/9/86tribologymachine learningartificial intelligencetriboinformaticsdatabasesdata mining |
| spellingShingle | Max Marian Stephan Tremmel Current Trends and Applications of Machine Learning in Tribology—A Review Lubricants tribology machine learning artificial intelligence triboinformatics databases data mining |
| title | Current Trends and Applications of Machine Learning in Tribology—A Review |
| title_full | Current Trends and Applications of Machine Learning in Tribology—A Review |
| title_fullStr | Current Trends and Applications of Machine Learning in Tribology—A Review |
| title_full_unstemmed | Current Trends and Applications of Machine Learning in Tribology—A Review |
| title_short | Current Trends and Applications of Machine Learning in Tribology—A Review |
| title_sort | current trends and applications of machine learning in tribology a review |
| topic | tribology machine learning artificial intelligence triboinformatics databases data mining |
| url | https://www.mdpi.com/2075-4442/9/9/86 |
| work_keys_str_mv | AT maxmarian currenttrendsandapplicationsofmachinelearningintribologyareview AT stephantremmel currenttrendsandapplicationsofmachinelearningintribologyareview |