The aim of the book based on the papers presented at the IV International Workshop Advances in Materials Science - AMS-IV 2024 (30-31 May 2024, Bukhara, Uzbekistan) was to encompass an examination of key themes in the latest materials science, integrating both theoretical frameworks and practical applications. The book highlights the mechanical properties of various materials, such as protective coatings and tool steels, emphasizing their behaviour under different processing techniques. It also explores advanced processing techniques, showcasing innovative manufacturing methods like direct metal deposition and CNC machining optimization. The application of nanotechnology is addressed, particularly regarding the influence of nanoparticles on wear resistance and mechanical properties. Furthermore, the integration of machine learning applications is discussed, focusing on how neural networks and deep learning can optimize material compositions and detect surface defects. Finally, the book investigates corrosion and wear resistance, tackling real-world challenges related to material durability in industrial settings. Overall, the edition aims to bridge the gap between theoretical research and industrial application, advancing knowledge in materials science.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Illustrationen
Dateigröße
ISBN-13
978-3-0364-1243-6 (9783036412436)
DOI
Schweitzer Klassifikation
Preface
Chapter 1: Steel and Alloys
Improvement of the Technology of Melting of Low Alloy Steel Alloy in an Electric Arc Furnace
Mathematical Modeling of the Effect of TiC Nanopowder Particles on the Wear Resistance Properties of Low-Alloy Steel
Study of Variability Phenomena in Direct Energy Deposition of Nickel-Based Superalloy on Geometric Accuracy and Residual Stress Formation
Chapter 2: Modern Approaches for Defect Detection
Automated Surface Defect Detection in Machined Parts Using Deep Learning Techniques and Machine Vision
Enhanced Surface Defect Detection in Industrial Manufacturing Using Convolutional Neural Networks and Advanced Imaging Techniques
Study of Trajectories Scattered Ar+ Ions from the CdTe(001) <110> at the Glancing Incidence
Chapter 3: Research and Design of Machines and Machine Parts
Enhancing Machine Tool Housing Design through Ultra High-Performance Concrete
Optimization of CNC Machining Tool Paths Using Reinforcement Learning Techniques
Enhancing CNC Machining Tool Path Planning through Reinforcement Learning and Optimization Techniques