The Special Issue Machining—Recent Advances, Applications and Challenges is intended as a humble collection of some of the hottest topics in machining. The manufacturing industry is a varying and challenging environment where new advances emerge from one day to another. In recent years, new manufacturing procedures have retained increasing attention from the industrial and scientific community. However, machining still remains the key operation to achieve high productivity and precision for high-added value parts. Continuous research is performed, and new ideas are constantly considered. This Special Issue summarizes selected high-quality papers which were submitted, peer-reviewed, and recommended by experts. It covers some (but not only) of the following topics: High performance operations for difficult-to-cut alloys, wrought and cast materials, light alloys, ceramics, etc.; Cutting tools, grades, substrates and coatings. Wear damage; Advanced cooling in machining: Minimum quantity of lubricant, dry or cryogenics; Modelling, focused on the reduction of risks, the process outcome, and to maintain surface integrity; Vibration problems in machines: Active and passive/predictive methods, sources, diagnosis and avoidance; Influence of machining in new concepts of machine–tool, and machine static and dynamic behaviors; Machinability of new composites, brittle and emerging materials; Assisted machining processes by high-pressure, laser, US, and others; Introduction of new analytics and decision making into machining programming. We wish to thank the reviewers and staff from Materials for their comments, advice, suggestions and invaluable support during the development of this Special Issue.

This book constitutes the refereed proceedings of the 15th European PVM/MPI Users' Group Meeting held in Dublin, Ireland, in September 2008. The 29 revised full papers presented together with abstracts of 7 invited contributions, 1 tutorial paper and 8 poster papers were carefully reviewed and selected from 55 submissions. The papers are organized in topical sections on applications, collective operations, library internals, message passing for multi-core and mutlithreaded architectures, MPI datatypes, MPI I/O, synchronisation issues in point-to-point and one-sided communications, tools, and verification of message passing programs. The volume is rounded off with 4 contributions to the special ParSim session on current trends in numerical simulation for parallel engineering environments.

Metal machining is the most widespread metal-shaping process in the mechanical manufacturing industry. World-wide investment in metal machining tools increases year on year - and the wealth of nations can be judged by it. This text - the most up-to-date in the field - provides in-depth discussion of the theory and application of metal machining at an advanced level. It begins with an overview of the development of metal machining and its role in the current industrial environment and continues with a discussion of the theory and practice of machining. The underlying mechanics are analysed in detail and there are extensive chapters examining applications through a discussion of simulation and process control. "Metal Machining: Theory and Applications" is essential reading for senior undergraduates and postgraduates specialising in cutting technology. It is also an invaluable reference tool for professional engineers. Professors Childs, Maekawa, Obikawa and Yamane are four of the leading authorities on metal machining and have worked together for many years.Of interest to all mechanical, manufacturing and materials engineersTheoretical and practical problems addressed

Advanced Machining Processes of Metallic Materials: Theory, Modelling and Applications, Second Edition, explores the metal cutting processes with regard to theory and industrial practice. Structured into three parts, the first section provides information on the fundamentals of machining, while the second and third parts include an overview of the effects of the theoretical and experimental considerations in high-level machining technology and a summary of production outputs related to part quality. In particular, topics discussed include: modern tool materials, mechanical, thermal and tribological aspects of machining, computer simulation of various process phenomena, chip control, monitoring of the cutting state, progressive and hybrid machining operations, as well as practical ways for improving machinability and generation and modeling of surface integrity. This new edition addresses the present state and future development of machining technologies, and includes expanded coverage on machining operations, such as turning, milling, drilling, and broaching, as well as a new chapter on sustainable machining processes. In addition, the book provides a comprehensive description of metal cutting theory and experimental and modeling techniques, along with basic machining processes and their effective use in a wide range of manufacturing applications. The research covered here has contributed to a more generalized vision of machining technology, including not only traditional manufacturing tasks, but also potential (emerging) new applications, such as micro and nanotechnology. - Includes new case studies illuminate experimental methods and outputs from different sectors of the manufacturing industry - Presents metal cutting processes that would be applicable for various technical, engineering, and scientific levels - Includes an updated knowledge of standards, cutting tool materials and tools, new machining technologies, relevant machinability records, optimization techniques, and surface integrity

Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.

Machine learning continues to have myriad applications across industries and fields. To ensure this technology is utilized appropriately and to its full potential, organizations must better understand exactly how and where it can be adapted. Further study on the applications of machine learning is required to discover its best practices, challenges, and strategies. The Research Anthology on Machine Learning Techniques, Methods, and Applications provides a thorough consideration of the innovative and emerging research within the area of machine learning. The book discusses how the technology has been used in the past as well as potential ways it can be used in the future to ensure industries continue to develop and grow. Covering a range of topics such as artificial intelligence, deep learning, cybersecurity, and robotics, this major reference work is ideal for computer scientists, managers, researchers, scholars, practitioners, academicians, instructors, and students.

Traditional machining has many limitations in today’s technology-driven world, which has caused industrial professionals to begin implementing various optimization techniques within their machining processes. The application of methods including machine learning and genetic algorithms has recently transformed the manufacturing industry and created countless opportunities in non-traditional machining methods. Significant research in this area, however, is still considerably lacking. Machine Learning Applications in Non-Conventional Machining Processes is a collection of innovative research on the advancement of intelligent technology in industrial environments and its applications within the manufacturing field. While highlighting topics including evolutionary algorithms, micro-machining, and artificial neural networks, this book is ideally designed for researchers, academicians, engineers, managers, developers, practitioners, industrialists, and students seeking current research on intelligence-based machining processes in today’s technology-driven market.

Quantum computers are unparalleled in terms of computational power, and they have a multitude of promising applications. However, these computers are prone to noise and instability caused by environmental interactions, making the use of these advanced machines rather impractical in most scenarios. Despite these challenges, Real-World Challenges in Quantum Electronics and Machine Computing provides innovative solutions to navigate the complexities of quantum computation, thus offering hope during this time of turbulence. By delving into the intricacies of quantum electronics and machine computing, this book equips readers with the tools to overcome the hurdles obstructing the path to practical quantum computing. It serves as a roadmap for students, practitioners, and professionals, guiding them through the intricacies of error correction techniques and hardware development. With its comprehensive coverage of cutting-edge topics and innovative solutions, the book empowers readers to tackle the most pressing challenges facing the quantum computing landscape. As researchers and engineers strive to unlock the full potential of quantum computation, this book stands as an indispensable resource, guiding them toward a future where quantum computing transcends the realm of theory and becomes a tangible reality.