Tin-Chih Toly Chen – författare

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 provides a thorough overview of the applications of 3D printing technologies to ubiquitous manufacturing (UM).

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.

Prevalent tools for lean manufacturing include Kanban, Pacemaker, Value Stream Map, 5s, Just-in-Time and Pull Manufacturing. Lean Manufacturing and the Toyota Manufacturing System has been successfully applied to various factories and supply chains around the world.

This book systematically analyzes the applicability of big data analytics and Industry 4.0 from the perspective of semiconductor manufacturing management. In recent years, technologies of big data analytics and Industry 4.0 have been frequently applied to the management of semiconductor manufacturing.

This book provides a comprehensive overview of the latest developments in Explainable AI (XAI) and its applications in manufacturing. With the increasing use of AI in manufacturing, there is a growing need to address the limitations of advanced AI methods that are difficult to understand or explain to those without a background in AI.

This book shows how smart technology applications to mobile healthcare will be different in the post-pandemic era. Prior to the Covid-19 pandemic, smart technologies had been widely applied to mobile health care. In addition, some innovative ways of applying smart technologies within the Covid-19 pandemic have emerged.

Dieses Buch wendet künstliche Intelligenz auf die schlanke Produktion an und zeigt, wie sich die Vorteile dieser beiden Disziplinen praktisch kombinieren lassen. Lean Manufacturing und das Toyota-Produktionssystem wurden in verschiedenen Fabriken und Lieferketten auf der ganzen Welt erfolgreich eingesetzt.

Dieses Buch bietet einen umfassenden Überblick über die Anwendungen von 3D-Drucktechnologien in der allgegenwärtigen Fertigung (Ubiquitous Manufacturing, UM). UM selbst stellt eine Anwendung des Ubiquitären Computings im Fertigungssektor dar, und dieses Buch zeigt, wie es bequemen, bedarfsgerechten Netzwerkzugang zu einem gemeinsamen Pool konfigurierbarer Fertigungsressourcen, einschließlich Software-Tools, Ausrüstung und Fähigkeiten, bietet.  Aufgrund seines Umfangs wird das Buch für Forscher in den Bereichen Fertigung, Maschinenbau, Betriebsmanagement, Produktionssteuerung, Ubiquitäres Computing und Sensortechnologien sowie für praktizierende Manager und Ingenieure von großem Interesse sein.

This book systematically reviews the progress of Explainable Ambient Intelligence (XAmI) and introduces its methods, tools, and applications.Ambient intelligence (AmI) is a vision in which an environment supports the people inhabiting it in an unobtrusive, interconnected, adaptable, dynamic, embedded, and intelligent way. So far, artificial intelligence (AI) technologies have been widely applied in AmI. However, some advanced AI methods are not easy to understand or communicate, especially for users with insufficient background knowledge of AI, which undoubtedly limits the practicability of these methods. To address this issue, explainable AI (XAI) has been considered a viable strategy. Although XAI technologies and tools applied in other fields can also be applied to explain AI technology applications in AmI, users should be the main body in the application of AmI, which is slightly different from the application of AI technologies in other fields.This book containsreal case studies of the application of XAml and is a valuable resource for students and researchers.

This book examines smart technologies and their invaluable role in augmenting the walking experience of mobile users.From meticulously planned walking routes to precise footprint detection and analysis, as well as cutting-edge fall detection and prevention mechanisms, these intelligent technologies have the potential to revolutionize healthy and smart walking. Against the backdrop of the post-COVID-19 era, where unrestricted mobility has become pivotal for restoring normalcy, the demand for smart healthcare solutions has soared.The book explores latest advances in sensor technology, cloud computing, deep learning, and networking and related innovative applications that can leverage smart technologies to enhance healthy walking.

This book provides a comprehensive exploration of semiconductor supply chain localization, offering insights into the formulation of effective strategies and ways to enhance the competitiveness and sustainability of semiconductor manufacturers through supply chain localization.The semiconductor industry is currently witnessing a significant localization wave, with a growing trend of wafer foundries relocating their production capacity closer to chip designers. This shift is primarily driven by factors such as the US-China trade war, geopolitical considerations, the impact of Covid-19, the Russia-Ukraine conflict, and the increasing importance of environmental awareness. By localizing semiconductor supply chains, companies can effectively address these challenges while also improving their competitive edge and ensuring long-term sustainability in the face of political and war risks.However, achieving supply chain localization in the semiconductor industry is a complex endeavor, as traditional factors considered in semiconductor supply chain management may no longer be decisive. Moreover, existing research on the subject is often scattered across various journal issues and conference proceedings, necessitating a systematic integration of these findings. Furthermore, most of the available supply chain management-related books do not specifically focus on this topic. This book aims to bridge these gaps by providing a comprehensive resource that combines relevant references, real-world cases, and supporting evidence.

This book provides a comprehensive exploration of semiconductor supply chain localization, offering insights into the formulation of effective strategies and ways to enhance the competitiveness and sustainability of semiconductor manufacturers through supply chain localization.The semiconductor industry is currently witnessing a significant localization wave, with a growing trend of wafer foundries relocating their production capacity closer to chip designers. This shift is primarily driven by factors such as the US-China trade war, geopolitical considerations, the impact of Covid-19, the Russia-Ukraine conflict, and the increasing importance of environmental awareness. By localizing semiconductor supply chains, companies can effectively address these challenges while also improving their competitive edge and ensuring long-term sustainability in the face of political and war risks.However, achieving supply chain localization in the semiconductor industry is a complex endeavor, as traditional factors considered in semiconductor supply chain management may no longer be decisive. Moreover, existing research on the subject is often scattered across various journal issues and conference proceedings, necessitating a systematic integration of these findings. Furthermore, most of the available supply chain management-related books do not specifically focus on this topic. This book aims to bridge these gaps by providing a comprehensive resource that combines relevant references, real-world cases, and supporting evidence.

This book systematically reviews the progress in explainable AI (XAI) and introduces the methods, tools, and applications of XAI technologies in job sequencing and scheduling.

This book systematically introduces the principles and latest developments in cycle time management. With the rise of artificial intelligence, numerous advanced information technologies, such as Industry 4.0, big data, edge computing, and explainable artificial intelligence, have emerged. Factory engineers are exploring opportunities to apply these technologies to enhance the efficiency and effectiveness of cycle time management. To address this, the book conducts a preliminary investigation and outlines several practical actions that can be implemented.Factories worldwide are striving to reduce cycle times to increase their competitiveness and sustainability. Cycle time modeling and factor analysis are essential prerequisites, followed by accurate cycle time prediction and stringent control measures. Reducing cycle times can offer a competitive advantage in managing customer relationships. The successful strategies for shortening cycle times can also be applied to other product types or factories, a concept known as cycle time learning. All these efforts rely on comprehensive cycle time management activities. This book will be of use to professionals in industry as well as researchers and graduate students.