Jagdeep Singh - Böcker

Internet of Healthcare Things (IoHT) is an Internet of Things (IoT)-based solution that includes a network architecture which allows the connection between a patient and healthcare facilities. This book covers various research issues of smart and secure IoHT, aimed at providing solutions for remote healthcare monitoring using pertinent techniques. Applications of machine learning techniques and data analytics in IoHT, along with the latest communication and networking technologies and cloud computing, are also discussed. Features: Provides a detailed introduction to IoHT and its applications Reviews underlying sensor and hardware technologies Includes recent advances in the IoHT, such as remote healthcare monitoring and wearable devices Explores applications of data analytics/data mining in IoHT, including data management and data governance Focuses on regulatory and compliance issues in IoHTThis book is intended for graduate students and researchers in Bioinformatics, Biomedical Engineering, Big Data and Analytics, Data Mining, and Information Management, IoT and Computer and Electrical Engineering.

Internet of Healthcare Things (IoHT) is an Internet of Things (IoT)-based solution that includes a network architecture which allows the connection between a patient and healthcare facilities. This book covers various research issues of smart and secure IoHT, aimed at providing solutions for remote healthcare monitoring using pertinent techniques. Applications of machine learning techniques and data analytics in IoHT, along with the latest communication and networking technologies and cloud computing, are also discussed. Features: Provides a detailed introduction to IoHT and its applications Reviews underlying sensor and hardware technologies Includes recent advances in the IoHT, such as remote healthcare monitoring and wearable devices Explores applications of data analytics/data mining in IoHT, including data management and data governance Focuses on regulatory and compliance issues in IoHTThis book is intended for graduate students and researchers in Bioinformatics, Biomedical Engineering, Big Data and Analytics, Data Mining, and Information Management, IoT and Computer and Electrical Engineering.

In the contemporary automotive manufacturing industry, service providers are continuously working to improve system optimization in order to remain competitive in the market and deliver quality products to satisfy their customers. With this comes the possibility of failure, rejection and reworking of the components or services in the system, which can incur high costs and impact the reputation of an organization. This book uses Failure Mode and Effect Analysis (FMEA) to assess, investigate and predict the Risk Priority Number (RPN) of potential failures for three companies within the manufacturing industry:A metal component supplier in the automotive sectorPart manufacturer for the automobile and engineering industriesManufacturer of suspension components for commercial vehiclesIntegrating human expertise and artificial intelligence on a single platform, the authors use fuzzy logic as a tool to overcome the vagueness associated with traditional methods of assessing potential failures. The book also details the procedure and scales of how to conduct FMEA, offering guidance on how to input and rank each risk within manufacturing processes across a range of sectors's. Each of the three real-world cases offer suggested improvements for the companies themselves, alongside takeaways for researchers and professionals within the fields of manufacturing and supply chain management.

This book presents the proceedings of the first International Upcycling Symposium 2020, held on 4th September 2020 at De Montfort University (DMU) in Leicester, UK (online), as a joint effort between DMU, Lund University, Nottingham Trent University and Newcastle University.

This book presents the proceedings of the first International Upcycling Symposium 2020, held on 4th September 2020 at De Montfort University (DMU) in Leicester, UK (online), as a joint effort between DMU, Lund University, Nottingham Trent University and Newcastle University.

This book covers the strategic use of continuous improvement (CI) techniques for manufacturing performance improvement. It focuses primarily on strategies that can be adopted by small and middle-sized enterprises in manufacturing in order to meet the global challenges and competition. The book begins with an introduction to CI (or Kaizen), explaining different CI approaches and strategies. Chapter 2 offers a literature review of CI, examining conceptual frameworks, case studies, and surveys. Next, the book deals with the design of the study, detailing the work done in each phase along with the tools, techniques and models. Chapter 4 presents a detailed survey to determine the present status of continuous improvement strategies in the Indian manufacturing industry, to assess the important barriers that effect the implementation of CI strategies, and to also assess the role of key enablers leading to improve the performance of manufacturing operations. Chapter 5 is comprised of detailedcase studies to further analyze the application of the discussed CI strategies. The purpose of Chapter 6 is to develop the relationship among the different identified most important barriers in implementing CI approach using interpretive structural modeling (ISM) and classify these barriers depending upon their driving and dependence power. Finally Chapter 7 provides conclusions, addresses potential limitations, and also looks to the future.