This book introduces the basic concepts of fuzzy collaborative forecasting and clustering, including its methodology, system architecture, and applications. It demonstrates how dealing with disparate data sources is becoming more and more popular due to the increasing spread of internet applications. The book proposes the concepts of collaborative computing intelligence and collaborative fuzzy modeling, and establishes several so-called fuzzy collaborative systems. It shows how technical constraints, security issues, and privacy considerations often limit access to some sources. This book is a valuable source of information for postgraduates, researchers and fuzzy control system developers, as it presents a very effective fuzzy approach that can deal with disparate data sources, big data, and multiple expert decision making.

This book is focused on fuzzy group decision making, offering technical details including methodology, collaboration and aggregation mechanisms, system architectures, and applications. It explores the two categories of fuzzy-group decision making - anterior-aggregation and posterior-aggregation - and highlights how imperative collaboration amongst decision makers is for both forms. Advances in Fuzzy Group Decision Making will be of interest to researchers in decision making, artificial intelligence, soft computing, operations management, and information management, as well as practicing managers and engineers.

This book provides a thorough overview of the applications of 3D printing technologies to ubiquitous manufacturing (UM). UM itself represents an application of ubiquitous computing in the manufacturing sector, and this book reveals how it offers convenient, on-demand network access to a shared pool of configurable manufacturing resources, including software tools, equipment, and capabilities. Given its scope, the book will be of considerable interest to researchers in the areas of manufacturing, mechanical engineering, operations management, production control, ubiquitous computing, and sensor technologies, as well as practicing managers and engineers.

This book systematically analyzes the applicability of big data analytics and Industry 4.0 from the perspective of semiconductor manufacturing management. It reports in real examples and presents case studies as supporting evidence. In recent years, technologies of big data analytics and Industry 4.0 have been frequently applied to the management of semiconductor manufacturing. However, related research results are mostly scattered in various journal issues or conference proceedings, and there is an urgent need for a systematic integration of these results. In addition, many related discussions have placed too much emphasis on the theoretical framework of information systems rather than on the needs of semiconductor manufacturing management. This book addresses these issues.