Название: Big Data Analytics in Smart Manufacturing: Principles and Practices
Автор: P Suresh, T Poongodi, B Balamurugan
Издательство: CRC Press
Год: 2022
Страниц: 205
Язык: английский
Формат: pdf (true)
Размер: 10.16 MB
Smart manufacturing analytics explores recent trends and affords a roadmap to adopt Big Data analytics for promoting various applications that range from fault detection processes to predictive maintenance activities. Big Data analytics has significantly changed and automated the data exchange processes with advanced manufacturing technologies. To remain competitive in the industrial domain, new methodologies of manufacturing, innovation, procurement, and logistics are adopted. This book covers the novel research work contribution of various pervasive applications from the authors in smart manufacturing. The main objective of this book is to gather relevant contributions for analyzing historical perspectives focusing on technological revolutions. Furthermore, theoretical concepts, principles, and practices of Big Data analytics in smart manufacturing are investigated with the original research analysis of different case studies. The characteristics, benefits, impacts, challenges, and opportunities of Big Data in design and manufacturing are also presented. Machine Learning (ML) discerned expanded utilization in commercial enterprise in the course of last many years. ML has stayed “depot” in each period of the item existence pattern: origination, plan, assembling, attribute, and preserve.
Автор: P Suresh, T Poongodi, B Balamurugan
Издательство: CRC Press
Год: 2022
Страниц: 205
Язык: английский
Формат: pdf (true)
Размер: 10.16 MB
Smart manufacturing analytics explores recent trends and affords a roadmap to adopt Big Data analytics for promoting various applications that range from fault detection processes to predictive maintenance activities. Big Data analytics has significantly changed and automated the data exchange processes with advanced manufacturing technologies. To remain competitive in the industrial domain, new methodologies of manufacturing, innovation, procurement, and logistics are adopted. This book covers the novel research work contribution of various pervasive applications from the authors in smart manufacturing. The main objective of this book is to gather relevant contributions for analyzing historical perspectives focusing on technological revolutions. Furthermore, theoretical concepts, principles, and practices of Big Data analytics in smart manufacturing are investigated with the original research analysis of different case studies. The characteristics, benefits, impacts, challenges, and opportunities of Big Data in design and manufacturing are also presented. Machine Learning (ML) discerned expanded utilization in commercial enterprise in the course of last many years. ML has stayed “depot” in each period of the item existence pattern: origination, plan, assembling, attribute, and preserve.