Author: Weidong Li
Publisher: Springer Nature
ISBN: 3030668495
Category : Technology & Engineering
Languages : en
Pages : 224
Book Description
This book reports innovative deep learning and big data analytics technologies for smart manufacturing applications. In this book, theoretical foundations, as well as the state-of-the-art and practical implementations for the relevant technologies, are covered. This book details the relevant applied research conducted by the authors in some important manufacturing applications, including intelligent prognosis on manufacturing processes, sustainable manufacturing and human-robot cooperation. Industrial case studies included in this book illustrate the design details of the algorithms and methodologies for the applications, in a bid to provide useful references to readers. Smart manufacturing aims to take advantage of advanced information and artificial intelligent technologies to enable flexibility in physical manufacturing processes to address increasingly dynamic markets. In recent years, the development of innovative deep learning and big data analytics algorithms is dramatic. Meanwhile, the algorithms and technologies have been widely applied to facilitate various manufacturing applications. It is essential to make a timely update on this subject considering its importance and rapid progress. This book offers a valuable resource for researchers in the smart manufacturing communities, as well as practicing engineers and decision makers in industry and all those interested in smart manufacturing and Industry 4.0.
Data Driven Smart Manufacturing Technologies and Applications
Author: Weidong Li
Publisher: Springer Nature
ISBN: 3030668495
Category : Technology & Engineering
Languages : en
Pages : 224
Book Description
This book reports innovative deep learning and big data analytics technologies for smart manufacturing applications. In this book, theoretical foundations, as well as the state-of-the-art and practical implementations for the relevant technologies, are covered. This book details the relevant applied research conducted by the authors in some important manufacturing applications, including intelligent prognosis on manufacturing processes, sustainable manufacturing and human-robot cooperation. Industrial case studies included in this book illustrate the design details of the algorithms and methodologies for the applications, in a bid to provide useful references to readers. Smart manufacturing aims to take advantage of advanced information and artificial intelligent technologies to enable flexibility in physical manufacturing processes to address increasingly dynamic markets. In recent years, the development of innovative deep learning and big data analytics algorithms is dramatic. Meanwhile, the algorithms and technologies have been widely applied to facilitate various manufacturing applications. It is essential to make a timely update on this subject considering its importance and rapid progress. This book offers a valuable resource for researchers in the smart manufacturing communities, as well as practicing engineers and decision makers in industry and all those interested in smart manufacturing and Industry 4.0.
Publisher: Springer Nature
ISBN: 3030668495
Category : Technology & Engineering
Languages : en
Pages : 224
Book Description
This book reports innovative deep learning and big data analytics technologies for smart manufacturing applications. In this book, theoretical foundations, as well as the state-of-the-art and practical implementations for the relevant technologies, are covered. This book details the relevant applied research conducted by the authors in some important manufacturing applications, including intelligent prognosis on manufacturing processes, sustainable manufacturing and human-robot cooperation. Industrial case studies included in this book illustrate the design details of the algorithms and methodologies for the applications, in a bid to provide useful references to readers. Smart manufacturing aims to take advantage of advanced information and artificial intelligent technologies to enable flexibility in physical manufacturing processes to address increasingly dynamic markets. In recent years, the development of innovative deep learning and big data analytics algorithms is dramatic. Meanwhile, the algorithms and technologies have been widely applied to facilitate various manufacturing applications. It is essential to make a timely update on this subject considering its importance and rapid progress. This book offers a valuable resource for researchers in the smart manufacturing communities, as well as practicing engineers and decision makers in industry and all those interested in smart manufacturing and Industry 4.0.
Big Data Analytics in Smart Manufacturing
Author: P Suresh
Publisher: CRC Press
ISBN: 1000815749
Category : Computers
Languages : en
Pages : 205
Book Description
The significant objective of this edited book is to bridge the gap between smart manufacturing and big data by exploring the challenges and limitations. Companies employ big data technology in the manufacturing field to acquire data about the products. Manufacturing companies could gain a deep business insight by tracking customer details, monitoring fuel consumption, detecting product defects, and supply chain management. Moreover, the convergence of smart manufacturing and big data analytics currently suffers due to data privacy concern, short of qualified personnel, inadequate investment, long-term storage management of high-quality data. The technological advancement makes the data storage more accessible, cheaper and the convergence of these technologies seems to be more promising in the recent era. This book identified the innovative challenges in the industrial domains by integrating heterogeneous data sources such as structured data, semi-structures data, geo-spatial data, textual information, multimedia data, social networking data, etc. It promotes data-driven business modelling processes by adopting big data technologies in the manufacturing industry. Big data analytics is emerging as a promising discipline in the manufacturing industry to build the rigid industrial data platforms. Moreover, big data facilitates process automation in the complete lifecycle of product design and tracking. This book is an essential guide and reference since it synthesizes interdisciplinary theoretical concepts, definitions, and models, involved in smart manufacturing domain. It also provides real-world scenarios and applications, making it accessible to a wider interdisciplinary audience. Features The readers will get an overview about the smart manufacturing system which enables optimized manufacturing processes and benefits the users by increasing overall profit The researchers will get insight about how the big data technology leverages in finding new associations, factors and patterns through data stream observations in real time smart manufacturing systems The industrialist can get an overview about the detection of defects in design, rapid response to market, innovative products to meet the customer requirement which can benefit their per capita income in better way Discusses technical viewpoints, concepts, theories, and underlying assumptions that are used in smart manufacturing Information delivered in a user-friendly manner for students, researchers, industrial experts, and business innovators, as well as for professionals and practitioners
Publisher: CRC Press
ISBN: 1000815749
Category : Computers
Languages : en
Pages : 205
Book Description
The significant objective of this edited book is to bridge the gap between smart manufacturing and big data by exploring the challenges and limitations. Companies employ big data technology in the manufacturing field to acquire data about the products. Manufacturing companies could gain a deep business insight by tracking customer details, monitoring fuel consumption, detecting product defects, and supply chain management. Moreover, the convergence of smart manufacturing and big data analytics currently suffers due to data privacy concern, short of qualified personnel, inadequate investment, long-term storage management of high-quality data. The technological advancement makes the data storage more accessible, cheaper and the convergence of these technologies seems to be more promising in the recent era. This book identified the innovative challenges in the industrial domains by integrating heterogeneous data sources such as structured data, semi-structures data, geo-spatial data, textual information, multimedia data, social networking data, etc. It promotes data-driven business modelling processes by adopting big data technologies in the manufacturing industry. Big data analytics is emerging as a promising discipline in the manufacturing industry to build the rigid industrial data platforms. Moreover, big data facilitates process automation in the complete lifecycle of product design and tracking. This book is an essential guide and reference since it synthesizes interdisciplinary theoretical concepts, definitions, and models, involved in smart manufacturing domain. It also provides real-world scenarios and applications, making it accessible to a wider interdisciplinary audience. Features The readers will get an overview about the smart manufacturing system which enables optimized manufacturing processes and benefits the users by increasing overall profit The researchers will get insight about how the big data technology leverages in finding new associations, factors and patterns through data stream observations in real time smart manufacturing systems The industrialist can get an overview about the detection of defects in design, rapid response to market, innovative products to meet the customer requirement which can benefit their per capita income in better way Discusses technical viewpoints, concepts, theories, and underlying assumptions that are used in smart manufacturing Information delivered in a user-friendly manner for students, researchers, industrial experts, and business innovators, as well as for professionals and practitioners
Intelligent Manufacturing Systems
Author: Andrew Kusiak
Publisher: Prentice Hall
ISBN: 9780134722344
Category : Computer integrated manufacturing systems
Languages : en
Pages : 443
Book Description
Defining structure and functions of knowledge-based systems, this book presents hardware and software components of flexible machining, flexible assembly and computer-integrated manufacturing systems. Discussed are such areas as process planning, group technology and lay-out design.
Publisher: Prentice Hall
ISBN: 9780134722344
Category : Computer integrated manufacturing systems
Languages : en
Pages : 443
Book Description
Defining structure and functions of knowledge-based systems, this book presents hardware and software components of flexible machining, flexible assembly and computer-integrated manufacturing systems. Discussed are such areas as process planning, group technology and lay-out design.
Big Data Analytics for Smart and Connected Cities
Author: Dey, Nilanjan
Publisher: IGI Global
ISBN: 1522562087
Category : Technology & Engineering
Languages : en
Pages : 371
Book Description
To continue providing people with safe, comfortable, and affordable places to live, cities must incorporate techniques and technologies to bring them into the future. The integration of big data and interconnected technology, along with the increasing population, will lead to the necessary creation of smart cities. Big Data Analytics for Smart and Connected Cities is a pivotal reference source that provides vital research on the application of the integration of interconnected technologies and big data analytics into the creation of smart cities. While highlighting topics such as energy conservation, public transit planning, and performance measurement, this publication explores technology integration in urban environments as well as the methods of planning cities to implement these new technologies. This book is ideally designed for engineers, professionals, researchers, and technology developers seeking current research on technology implementation in urban settings.
Publisher: IGI Global
ISBN: 1522562087
Category : Technology & Engineering
Languages : en
Pages : 371
Book Description
To continue providing people with safe, comfortable, and affordable places to live, cities must incorporate techniques and technologies to bring them into the future. The integration of big data and interconnected technology, along with the increasing population, will lead to the necessary creation of smart cities. Big Data Analytics for Smart and Connected Cities is a pivotal reference source that provides vital research on the application of the integration of interconnected technologies and big data analytics into the creation of smart cities. While highlighting topics such as energy conservation, public transit planning, and performance measurement, this publication explores technology integration in urban environments as well as the methods of planning cities to implement these new technologies. This book is ideally designed for engineers, professionals, researchers, and technology developers seeking current research on technology implementation in urban settings.
Big Data Applications in Industry 4.0
Author: P. Kaliraj
Publisher: CRC Press
ISBN: 1000537668
Category : Computers
Languages : en
Pages : 446
Book Description
Industry 4.0 is the latest technological innovation in manufacturing with the goal to increase productivity in a flexible and efficient manner. Changing the way in which manufacturers operate, this revolutionary transformation is powered by various technology advances including Big Data analytics, Internet of Things (IoT), Artificial Intelligence (AI), and cloud computing. Big Data analytics has been identified as one of the significant components of Industry 4.0, as it provides valuable insights for smart factory management. Big Data and Industry 4.0 have the potential to reduce resource consumption and optimize processes, thereby playing a key role in achieving sustainable development. Big Data Applications in Industry 4.0 covers the recent advancements that have emerged in the field of Big Data and its applications. The book introduces the concepts and advanced tools and technologies for representing and processing Big Data. It also covers applications of Big Data in such domains as financial services, education, healthcare, biomedical research, logistics, and warehouse management. Researchers, students, scientists, engineers, and statisticians can turn to this book to learn about concepts, technologies, and applications that solve real-world problems. Features An introduction to data science and the types of data analytics methods accessible today An overview of data integration concepts, methodologies, and solutions A general framework of forecasting principles and applications, as well as basic forecasting models including naïve, moving average, and exponential smoothing models A detailed roadmap of the Big Data evolution and its related technological transformation in computing, along with a brief description of related terminologies The application of Industry 4.0 and Big Data in the field of education The features, prospects, and significant role of Big Data in the banking industry, as well as various use cases of Big Data in banking, finance services, and insurance Implementing a Data Lake (DL) in the cloud and the significance of a data lake in decision making
Publisher: CRC Press
ISBN: 1000537668
Category : Computers
Languages : en
Pages : 446
Book Description
Industry 4.0 is the latest technological innovation in manufacturing with the goal to increase productivity in a flexible and efficient manner. Changing the way in which manufacturers operate, this revolutionary transformation is powered by various technology advances including Big Data analytics, Internet of Things (IoT), Artificial Intelligence (AI), and cloud computing. Big Data analytics has been identified as one of the significant components of Industry 4.0, as it provides valuable insights for smart factory management. Big Data and Industry 4.0 have the potential to reduce resource consumption and optimize processes, thereby playing a key role in achieving sustainable development. Big Data Applications in Industry 4.0 covers the recent advancements that have emerged in the field of Big Data and its applications. The book introduces the concepts and advanced tools and technologies for representing and processing Big Data. It also covers applications of Big Data in such domains as financial services, education, healthcare, biomedical research, logistics, and warehouse management. Researchers, students, scientists, engineers, and statisticians can turn to this book to learn about concepts, technologies, and applications that solve real-world problems. Features An introduction to data science and the types of data analytics methods accessible today An overview of data integration concepts, methodologies, and solutions A general framework of forecasting principles and applications, as well as basic forecasting models including naïve, moving average, and exponential smoothing models A detailed roadmap of the Big Data evolution and its related technological transformation in computing, along with a brief description of related terminologies The application of Industry 4.0 and Big Data in the field of education The features, prospects, and significant role of Big Data in the banking industry, as well as various use cases of Big Data in banking, finance services, and insurance Implementing a Data Lake (DL) in the cloud and the significance of a data lake in decision making
Research in Intelligent and Computing in Engineering
Author: Raghvendra Kumar
Publisher: Springer
ISBN: 9789811575266
Category : Technology & Engineering
Languages : en
Pages : 1007
Book Description
This book comprises select peer-reviewed proceedings of the international conference on Research in Intelligent and Computing in Engineering (RICE 2020) held at Thu Dau Mot University, Vietnam. The volume primarily focuses on latest research and advances in various computing models such as centralized, distributed, cluster, grid, and cloud computing. Practical examples and real-life applications of wireless sensor networks, mobile ad hoc networks, and internet of things, data mining and machine learning are also covered in the book. The contents aim to enable researchers and professionals to tackle the rapidly growing needs of network applications and the various complexities associated with them.
Publisher: Springer
ISBN: 9789811575266
Category : Technology & Engineering
Languages : en
Pages : 1007
Book Description
This book comprises select peer-reviewed proceedings of the international conference on Research in Intelligent and Computing in Engineering (RICE 2020) held at Thu Dau Mot University, Vietnam. The volume primarily focuses on latest research and advances in various computing models such as centralized, distributed, cluster, grid, and cloud computing. Practical examples and real-life applications of wireless sensor networks, mobile ad hoc networks, and internet of things, data mining and machine learning are also covered in the book. The contents aim to enable researchers and professionals to tackle the rapidly growing needs of network applications and the various complexities associated with them.
Smart Manufacturing
Author: Masoud Soroush
Publisher: Elsevier
ISBN: 0128203803
Category : Technology & Engineering
Languages : en
Pages : 428
Book Description
Research efforts in the past ten years have led to considerable advances in the concepts and methods of smart manufacturing. Smart Manufacturing: Concepts and Methods puts these advances in perspective, showing how process industries can benefit from these new techniques. The book consolidates results developed by leading academic and industrial groups in the area, providing a systematic, comprehensive coverage of conceptual and methodological advances made to date. Written by leaders in the field from around the world, Smart Manufacturing: Concepts and Methods is essential reading for graduate students, researchers, process engineers, and managers. It is complemented by a companion book titled Smart Manufacturing: Applications and Case Studies, which covers the applications of smart manufacturing concepts and methods in process industries and beyond. - Takes a process-systems engineering approach to design, monitoring, and control of smart manufacturing systems - Brings together the key concepts and methods of smart manufacturing, including the advances made in the past decade - Includes coverage of computation methods for process optimization, control, and safety, as well as advanced modelling techniques
Publisher: Elsevier
ISBN: 0128203803
Category : Technology & Engineering
Languages : en
Pages : 428
Book Description
Research efforts in the past ten years have led to considerable advances in the concepts and methods of smart manufacturing. Smart Manufacturing: Concepts and Methods puts these advances in perspective, showing how process industries can benefit from these new techniques. The book consolidates results developed by leading academic and industrial groups in the area, providing a systematic, comprehensive coverage of conceptual and methodological advances made to date. Written by leaders in the field from around the world, Smart Manufacturing: Concepts and Methods is essential reading for graduate students, researchers, process engineers, and managers. It is complemented by a companion book titled Smart Manufacturing: Applications and Case Studies, which covers the applications of smart manufacturing concepts and methods in process industries and beyond. - Takes a process-systems engineering approach to design, monitoring, and control of smart manufacturing systems - Brings together the key concepts and methods of smart manufacturing, including the advances made in the past decade - Includes coverage of computation methods for process optimization, control, and safety, as well as advanced modelling techniques
Guide to Industrial Analytics
Author: Richard Hill
Publisher: Springer Nature
ISBN: 3030791041
Category : Computers
Languages : en
Pages : 285
Book Description
This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments. This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use. Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation.
Publisher: Springer Nature
ISBN: 3030791041
Category : Computers
Languages : en
Pages : 285
Book Description
This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments. This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use. Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation.
Smart Manufacturing
Author: Masoud Soroush
Publisher: Elsevier
ISBN: 0128203811
Category : Technology & Engineering
Languages : en
Pages : 530
Book Description
Research efforts in the past decade have led to considerable advances in the concepts and methods of smart manufacturing. Smart Manufacturing: Applications and Case Studies includes information about the key applications of these new methods, as well as practitioners' accounts of real-life applications and case studies. Written by thought leaders in the field from around the world, Smart Manufacturing: Applications and Case Studies is essential reading for graduate students, researchers, process engineers and managers. It is complemented by a companion book titled Smart Manufacturing: Concepts and Methods, which describes smart manufacturing methods in detail. - Includes examples of applications of smart manufacturing in process industries - Provides a thorough overview of the subject and practical examples of applications through well researched case studies - Offers insights and accounts of first-hand experiences to motivate further implementations of the key concepts of smart manufacturing
Publisher: Elsevier
ISBN: 0128203811
Category : Technology & Engineering
Languages : en
Pages : 530
Book Description
Research efforts in the past decade have led to considerable advances in the concepts and methods of smart manufacturing. Smart Manufacturing: Applications and Case Studies includes information about the key applications of these new methods, as well as practitioners' accounts of real-life applications and case studies. Written by thought leaders in the field from around the world, Smart Manufacturing: Applications and Case Studies is essential reading for graduate students, researchers, process engineers and managers. It is complemented by a companion book titled Smart Manufacturing: Concepts and Methods, which describes smart manufacturing methods in detail. - Includes examples of applications of smart manufacturing in process industries - Provides a thorough overview of the subject and practical examples of applications through well researched case studies - Offers insights and accounts of first-hand experiences to motivate further implementations of the key concepts of smart manufacturing
New Horizons for a Data-Driven Economy
Author: José María Cavanillas
Publisher: Springer
ISBN: 3319215698
Category : Computers
Languages : en
Pages : 312
Book Description
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.
Publisher: Springer
ISBN: 3319215698
Category : Computers
Languages : en
Pages : 312
Book Description
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.