Broadens understanding of manufacturing clusters in the environment of Internet of Things
Equips readers to handle complex models, algorithms, and methods used to process a high volume of data
Offers solutions to traditional resource collaborative optimization and management problems
Broadens understanding of manufacturing clusters in the environment of Internet of Things
Equips readers to handle complex models, algorithms, and methods used to process a high volume of data
Offers solutions to traditional resource collaborative optimization and management problems
Includes supplementary material: sn.pub/extras
Problems facing manufacturing clusters that intersect information technology, process management, and optimization within the Internet of Things (IoT) are examined in this book. Recent advances in information technology have transformed the use of resources and data exchange, often leading to management and optimization problems attributatble to technology limitations and strong market competition. This book discusses several problems and concepts which makes significant connections in the areas of information sharing, organization management, resource operations, and performance assessment.
Geared toward practitioners and researchers, this treatment deepens the understanding between resource collaborative management and advanced information technology. Those in manufacturing will utilize the numerous mathematical models and methods offered to solve practical problems related to cutting stock, supply chain scheduling, and inventory management. Academics and students with a basic knowledge of manufacturing, combinatorics, and linear programming will find that this discussion widens the research area of resource collaborative management and unites the fields of information technology, manufacturing management, and optimization.
1. Information Sharing and Risk Management.- 2. Optimal Allocation of Decision-Making Authority in IoT-based Manufacturing Enterprises.- 3. Dynamic Coordinated Supply Chain Scheduling in an IoT Environment.- 4. Hybrid Manufacturing Distributed Inventory Management with Sharing Logistics.- 5. Cutting stock problem with the IoT.- 6. Total Quality Management of the Product Life Cycle in an IoT Environment.- 7. Life Cycle Assessment in an IoT Environment. –References.
Problems facing manufacturing clusters that intersect information technology, process management, and optimization within the Internet of Things (IoT) are examined in this book. Recent advances in information technology have transformed the use of resources and data exchange, often leading to management and optimization problems attributable to technology limitations and strong market competition. This book discusses several problems and concepts which makes significant connections in the areas of information sharing, organization management, resource operations, and performance assessment.
Geared toward practitioners and researchers, this treatment deepens the understanding between resource collaborative management and advanced information technology. Those in manufacturing will utilize the numerous mathematical models and methods offered to solve practical problems related to cutting stock, supply chain scheduling, and inventory management. Academics and students with a basic knowledge of manufacturing, combinatorics, and linear programming will find that this discussion widens the research area of resource collaborative management and unites the fields of information technology, manufacturing management, and optimization.
"This is an interesting and timely book that examines the challenges faced by manufacturing systems that integrate information technology, process management, and optimization within the Internet of Things (IoT). It should be required reading for anyone who is interested in new trends in optimization and management in manufacturing engineering that are being driven by the recent advances in the Internet of Things through the ever-expanding role of the internet and big data.” (Ignacio E. Grossmann, Optimization Methods and Software, Vol. 34 (1), 2019)
"This book provides numerous practical examples that managers can use currently or adapt into their plans as their IoT capabilities increase. It also gives academic researchers a solid foundation on which to create additional contributions to this burgeoning area of investigation.” (John R. Birge, Journal of Global Optimization, Vol. 73, 2019)
Problems facing manufacturing clusters that intersect information technology, process management, and optimization within the Internet of Things (IoT) are examined in this book. Recent advances in information technology have transformed the use of resources and data exchange, often leading to management and optimization problems attributatble to technology limitations and strong market competition. This book discusses several problems and concepts which makes significant connections in the areas of information sharing, organization management, resource operations, and performance assessment.
Geared toward practitioners and researchers, this treatment deepens the understanding between resource collaborative management and advanced information technology. Those in manufacturing will utilize the numerous mathematical models and methods offered to solve practical problems related to cutting stock, supply chain scheduling, and inventory management. Academics and students with a basic knowledge of manufacturing, combinatorics, and linear programming will find that this discussion widens the research area of resource collaborative management and unites the fields of information technology, manufacturing management, and optimization.
1. Information Sharing and Risk Management.- 2. Optimal Allocation of Decision-Making Authority in IoT-based Manufacturing Enterprises.- 3. Dynamic Coordinated Supply Chain Scheduling in an IoT Environment.- 4. Hybrid Manufacturing Distributed Inventory Management with Sharing Logistics.- 5. Cutting stock problem with the IoT.- 6. Total Quality Management of the Product Life Cycle in an IoT Environment.- 7. Life Cycle Assessment in an IoT Environment. -References.
"This is an interesting and timely book that examines the challenges faced by manufacturing systems that integrate information technology, process management, and optimization within the Internet of Things (IoT). It should be required reading for anyone who is interested in new trends in optimization and management in manufacturing engineering that are being driven by the recent advances in the Internet of Things through the ever-expanding role of the internet and big data." (Ignacio E. Grossmann, Optimization Methods and Software, Vol. 34 (1), 2019)
"This book provides numerous practical examples thatmanagers can use currently or adapt into their plans as their IoT capabilities increase. It also gives academic researchers a solid foundation on which to create additional contributions to this burgeoning area of investigation." (John R. Birge, Journal of Global Optimization, Vol. 73, 2019)
Inhaltsverzeichnis
1. Information Sharing and Risk Management.- 2. Optimal Allocation of Decision-Making Authority in IoT-based Manufacturing Enterprises.- 3. Dynamic Coordinated Supply Chain Scheduling in an IoT Environment.- 4. Hybrid Manufacturing Distributed Inventory Management with Sharing Logistics.- 5. Cutting stock problem with the IoT.- 6. Total Quality Management of the Product Life Cycle in an IoT Environment.- 7. Life Cycle Assessment in an IoT Environment. -References.
Klappentext
Problems facing manufacturing clusters that intersect information technology, process management, and optimization within the Internet of Things (IoT) are examined in this book. Recent advances in information technology have transformed the use of resources and data exchange, often leading to management and optimization problems attributatble to technology limitations and strong market competition. This book discusses several problems and concepts which makes significant connections in the areas of information sharing, organization management, resource operations, and performance assessment.Geared toward practitioners and researchers, this treatment deepens the understanding between resource collaborative management and advanced information technology. Those in manufacturing will utilize the numerous mathematical models and methods offered to solve practical problems related to cutting stock, supply chain scheduling, and inventory management. Academics and students with a basic knowledge of manufacturing, combinatorics, and linear programming will find that this discussion widens the research area of resource collaborative management and unites the fields of information technology, manufacturing management, and optimization.
Broadens understanding of manufacturing clusters in the environment of Internet of Things
Equips readers to handle complex models, algorithms, and methods used to process a high volume of data
Offers solutions to traditional resource collaborative optimization and management problems
Includes supplementary material: sn.pub/extras
