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April 7, 2026Lubricants2 citationsOpen Access

New Horizons in Machine Learning Applications for Tribology

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MMMax MarianSTS. Tremmel

Key Points

  • To investigate the role of machine learning in improving tribological performance metrics.
  • Review of existing machine learning techniques applied to tribology
  • Analysis of friction and wear data using predictive algorithms
  • Assessment of lubrication efficiency with machine learning models
  • Machine learning models significantly improve accuracy in predicting friction behavior
  • Enhanced wear analysis leads to better material selection
  • Improved lubrication strategies are suggested through data-driven insights

Abstract

Tribology, the science of friction, wear, and lubrication, remains fundamental to modern engineering systems ...

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Cite This Study

Marian et al. (2026) studied this question.

synapsesocial.com/papers/69d49fe5b33cc4c35a228587https://doi.org/10.3390/lubricants14040155
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Recent Advances in Machine Learning in Tribology2024 · 7 citations
  2. 2Tribology of Textured Surfaces2025
  3. 3Future research directions and applications of artificial intelligence in tribology2026 · 1 citations
  4. 4Special Issue on Laser Surface Engineering for Tribology2024 · 4 citations
  5. 5Enhancing tribological system performance through intelligent data analysis and predictive modeling: A review2025