Journal
FRICTION
Volume 11, Issue 1, Pages 1-22Publisher
SPRINGER
DOI: 10.1007/s40544-022-0596-7
Keywords
tribo-informatics; data-driven; artificial intelligence; information technology; machine learning
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Tribology research focuses on friction, wear, and lubrication between interacting surfaces. It has gone through stages of empirical, theoretical, and computational approaches. With the development of information technology, the field of tribology has introduced the concept of tribo-informatics. This paper reviews the application of tribo-informatics methods in tribology research, aiming to provide guidance for efficient and scientific research in this field.
Tribology research mainly focuses on the friction, wear, and lubrication between interacting surfaces. With the continuous increase in the industrialization of human society, tribology research objects have become increasingly extensive. Tribology research methods have also gone through the stages of empirical science based on phenomena, theoretical science based on models, and computational science based on simulations. Tribology research has a strong engineering background. Owing to the intense coupling characteristics of tribology, tribological information includes subject information related to mathematics, physics, chemistry, materials, machinery, etc. Constantly emerging data and models are the basis for the development of tribology. The development of information technology has provided new and more efficient methods for generating, collecting, processing, and analyzing tribological data. As a result, the concept of tribo-informatics (triboinformatics) has been introduced. In this paper, guided by the framework of tribo-informatics, the application of tribo-informatics methods in tribology is reviewed. This article aims to provide helpful guidance for efficient and scientific tribology research using tribo-informatics approaches.
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