Artificial Intelligence in Tribology presents the use of machine learning, AI, neural networks, and optimization algorithms in studying friction, wear, and lubrication. It explores the selection of materials, modeling of the tribo‑system, prediction of tribological behavior, and assessment and optimization of performance across numerous systems.

Addressing tribological problems from macroscale to nanoparticles, this book discusses AI‑driven methods to improve productivity, detect disasters, and support sustainable engineering. Case studies from various industries, such as automotive, aerospace, renewable energy, and marine engineering, highlight the transformative impact of AI in real‑world scenarios.

This book will interest researchers and graduate students studying AI integration and advances in surface engineering, tribology, and materials science.

Artificial Intelligence in Tribology presents the use of machine learning, AI, neural networks, and optimization algorithms in studying friction, wear, and lubrication. It explores the selection of materials, modeling of the tribo‑system, prediction of tribological behavior, and assessment and optimization of performance across numerous systems.

Addressing tribological problems from macroscale to nanoparticles, this book discusses AI‑driven methods to improve productivity, detect disasters, and support sustainable engineering. Case studies from various industries, such as automotive, aerospace, renewable energy, and marine engineering, highlight the transformative impact of AI in real‑world scenarios.

This book will interest researchers and graduate students studying AI integration and advances in surface engineering, tribology, and materials science.

Artificial Intelligence in Tribology presents the use of machine learning, AI, neural networks, and optimization algorithms in studying friction, wear, and lubrication. It explores the selection of materials, modeling of the tribo‑system, prediction of tribological behavior, and assessment and optimization of performance across numerous systems.

Addressing tribological problems from macroscale to nanoparticles, this book discusses AI‑driven methods to improve productivity, detect disasters, and support sustainable engineering. Case studies from various industries, such as automotive, aerospace, renewable energy, and marine engineering, highlight the transformative impact of AI in real‑world scenarios.

This book will interest researchers and graduate students studying AI integration and advances in surface engineering, tribology, and materials science.