The Use of Artificial Intelligence in Tribology-A Perspective

Artificial intelligence and, in particular, machine learning methods have gained notable attention in the tribological community due to their ability to predict tribologically relevant parameters such as, for instance, the coefficient of friction or the oil film thickness. This perspective aims at highlighting some of the recent advances achieved by implementing artificial intelligence, specifically artificial neutral networks, towards tribological research. The presentation and discussion of successful case studies using these approaches in a tribological context clearly demonstrates their ability to accurately and efficiently predict these tribological characteristics. Regarding future research directions and trends, we emphasis on the extended use of artificial intelligence and machine learning concepts in the field of tribology including the characterization of the resulting surface topography and the design of lubricated systems.

Automated summary

This article introduces the application of artificial intelligence and machine learning in the field of tribology, highlighting recent advances and successful case studies using artificial neural networks. These methods demonstrate accurate and efficient prediction of tribological characteristics, with future research directions emphasizing the extended use of artificial intelligence and machine learning concepts.