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This monograph analyzes the evolution of metal cutting technologies through the integration of artificial intelligence, data-driven optimization, and adaptive control. The author examines how machine learning models, sensor-enhanced monitoring, and hybrid human-AI decision systems transform precision cutting, tool wear prediction, process stability, and quality assurance. The book presents conceptual frameworks and practical methodologies that support the transition from traditional steel processing to intelligent, self-optimizing manufacturing systems. It offers a forward-looking perspective…mehr

Produktbeschreibung
This monograph analyzes the evolution of metal cutting technologies through the integration of artificial intelligence, data-driven optimization, and adaptive control. The author examines how machine learning models, sensor-enhanced monitoring, and hybrid human-AI decision systems transform precision cutting, tool wear prediction, process stability, and quality assurance. The book presents conceptual frameworks and practical methodologies that support the transition from traditional steel processing to intelligent, self-optimizing manufacturing systems. It offers a forward-looking perspective on how AI reshapes modern metalworking and enables more efficient, reliable, and high-performance production environments.
Autorenporträt
Viacheslav Shargaev is an innovation leader in metallurgy whose research explores artificial intelligence and human-machine collaboration. He authors works on intelligent, efficient and future-oriented industrial systems.