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Showing 1 - 6 of 6 matches in All Departments
This book presents the select proceedings of the International Conference on Evolution in Manufacturing (ICEM 2020), and examines a range of areas including evolution in manufacturing, intelligent networks, bio-Inspired models and algorithms, internet-of-things, and cyber manufacturing. This book intends to provide a contribution to the domain of collaborative and intelligent networks and systems to fill the gap in theories and practical applications through suitable methods and solutions applicable to a wide range of instances. Various topics covered include broad range of research challenges in the fields of artificial intelligence and addressing current and future trends in industry 4.0 oriented scenario, data analytics and big data, operation and manufacturing management. The book will be a valuable reference for beginners, researchers and professionals interested in artificial intelligence in engineering and production management and allied fields.
The current perspectives of smart and sustainable manufacturing systems hold important implications for current practices and understanding these concepts for further implications. This comprehensive reference text discusses both centralized and decentralized production systems, using variety of new cutting-edge approaches to solve the problem. The text covers simulation-based approaches including social network-based approaches, discrete event-based approaches, and knowledge based for smart and sustainable systems. It further covers mathematical models such as single-objective, multi-objective, and many-objective. The text discusses important topics including energy efficiency, transportation constrains for efficient and effective production, meta-heuristic and hybrid algorithms, and real-time monitoring and analysis for smart and sustainable production. This book- * Presents approaches to improve the objectives of sustain-ability and smart production systems. * Discusses Internet of Things (IoT) and Industrial Internet of Things (IIoT) concepts and its implementation for production systems. * Covers social network analysis method in distributed manufacturing systems. * Examines reckoning prognostics and diagnostics to monitor the health of the systems in perspective of distributed manufacturing. * Discusses aspects of Industry 4.0 in specific production systems. The text will be useful for graduate students and professional in the fields of mechanical engineering, production engineering, industrial engineering, and manufacturing.
This book presents select proceedings of the International Conference on Evolution in Manufacturing (ICEM 2020), and examines a range of areas including internet-of-things for cyber manufacturing, data analytics for manufacturing systems and processes and materials. The topics covered include modeling simulation and decision making in cyber physical systems for supporting engineering and production management, innovative approach in materials development, biomaterial applications, and advancement in manufacturing and material technologies. The book also discusses sustainability in manufacturing and supply chain management including circular economy. The book will be a valuable reference for beginners, researchers, and professionals interested in smart manufacturing in engineering, production management and materials technology.
This book presents select proceedings of the International Conference on Evolution in Manufacturing (ICEM 2020), and examines a range of areas including internet-of-things for cyber manufacturing, data analytics for manufacturing systems and processes and materials. The topics covered include modeling simulation and decision making in cyber physical systems for supporting engineering and production management, innovative approach in materials development, biomaterial applications, and advancement in manufacturing and material technologies. The book also discusses sustainability in manufacturing and supply chain management including circular economy. The book will be a valuable reference for beginners, researchers, and professionals interested in smart manufacturing in engineering, production management and materials technology.
This book covers a variety of topics in the field of industrial engineering, with a special focus on research and industrial applications aimed at both improving quality of processes and products and contributing to a sustainable economy. Based on a set of papers presented at the 2nd International Conference "Innovation in Engineering", ICIE, held in Minho, Portugal, on June 28-30, 2022, it focuses on innovative technologies associated with and strategies for the development of Industry 4.0. The chapters discuss new ways to improve industrial production and supply chain management by applying mathematical and computational methods. They also cover important issues relating to sustainability, education, and collaborations between industry and universities, and national developments. This book, which belongs to a three-volume set, provides engineering researchers and professionals with a timely overview and extensive information on trends and technologies behind the current and future developments of Industry 4.0.
This book presents the select proceedings of the International Conference on Evolution in Manufacturing (ICEM 2020), and examines a range of areas including evolution in manufacturing, intelligent networks, bio-Inspired models and algorithms, internet-of-things, and cyber manufacturing. This book intends to provide a contribution to the domain of collaborative and intelligent networks and systems to fill the gap in theories and practical applications through suitable methods and solutions applicable to a wide range of instances. Various topics covered include broad range of research challenges in the fields of artificial intelligence and addressing current and future trends in industry 4.0 oriented scenario, data analytics and big data, operation and manufacturing management. The book will be a valuable reference for beginners, researchers and professionals interested in artificial intelligence in engineering and production management and allied fields.
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