Due to problems associated with the design and manufacturing of composite materials, there is a need to introduce computational and intelligent systems engineering methodology in materials engineering. Soft Computing in the Design and Manufacturing of Composite Material offers an intelligent approach to advance material engineering, and significantly improves the process of designing and manufacturing a new material. This title includes chapters covering topics such as soft computing techniques, composite materials engineering, design and manufacturing of composite materials, numerical modeling, prediction, and optimization of the composite materials performance, development of the hybrid models, and control of the composite material performance. Introduction of soft computing in the composite materials engineering Includes accurate and detailed analysis of the current state of the art in the field Development of the intelligent models for design and manufacturing of composite material Details composite material performance prediction Optimization of the manufacturing process of composite materials

This book aims at addressing the challenges of contemporary manufacturing in Industry 4.0 environment and future manufacturing (aka Industry 5.0), by implementing soft computing as one of the major sub-fields of artificial intelligence. It contributes to development and application of the soft computing systems, including links to hardware, software and enterprise systems, in resolving modern manufacturing issues in complex, highly dynamic and globalized industrial circumstances. It embraces heterogeneous complementary aspects, such as control, monitoring and modeling of different manufacturing tasks, including intelligent robotic systems and processes, addressed by various machine learning and fuzzy techniques; modeling and parametric optimization of advanced conventional and non-conventional, eco-friendly manufacturing processes by using machine learning and evolutionary computing techniques; cybersecurity framework for Internet of Things-based systems addressing trustworthiness and resilience in machine-to-machine and human-machine collaboration; static and dynamic digital twins integration and synchronization in a smart factory environment; STEP-NC technology for a smart machine vision system, and integration of Open CNC with Service-Oriented Architecture for STEP-NC monitoring system in a smart manufacturing. Areas of interest include but are not limited to applications of soft computing to address the following: dynamic process/system modeling and simulation, dynamic process/system parametric optimization, dynamic planning and scheduling, smart, predictive maintenance, intelligent and autonomous systems, improved machine cognition, effective digital twins integration, human-machine collaboration, robots, and cobots.

Describes the individual capabilities of each of 1,900 unique resources in the federal laboratory system, and provides the name and phone number of each contact. Includes government laboratories, research centers, testing facilities, and special technology information centers. Also includes a list of all federal laboratory technology transfer offices. Organized into 72 subject areas. Detailed indices.

This book focuses on the application of soft computing in materials and manufacturing sectors with the objective to offer an intelligent approach to improve the manufacturing process, material selection and characterization techniques for developing advanced new materials. It unveils different models and soft computing techniques applicable in the field of advanced materials and solves the problems to help the industry and scientists to develop sustainable materials for all purposes. The book focuses on the overall well-being of the environment for better sustenance and livelihood. Firstly, the authors discuss the implementation of soft computing in the various areas of engineering materials. They also review the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and effective implementation of sustainable engineering practices. Finally the authors examine the future generation of sustainable and intelligent monitoring techniques beneficial for manufacturing, and cover novel soft computing techniques for the purpose of effective manufacturing processes at par with the standards laid down by the International Standards of Organization (ISO). This book is intended for academics and researchers from all the fields of engineering interested in joining interdisciplinary initiatives on soft computing techniques for advanced materials and manufacturing.

This book offers a selection of the best papers presented at the annual international scientific conference “Digital Transformation in Industry: Trends, Management, Strategies (DTI2021),” held by the Institute of Economics, Ural Branch of the Russian Academy of Sciences, in Ekaterinburg (Russia) on October 29, 2021. The book focuses on the idea of introduction mechanisms for digitization processes and on highlighting successful digital transformation strategies in all sectors of industry. Key topics include the development of a cyber-physical production system for Industry 4.0; digital design technologies for enhancing the competitiveness of products and companies; digital twin-driven product manufacturing and services; and the effects of the industrial digital transformation on society and the environment. With regard to implementing IT and other technological innovations, lessons learned in developed and developing economies, as well as small and large enterprises, are included. Given its scope, the book offers a valuable asset for researchers and managers of industrial organizations alike.

Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.