rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Big data analytics in smart manufacturing
    sub title: principles and practices
  name:
    name part: Suresh, P.
    name part: 1983-
    role:
      role term: editor.
  name:
    name part: Poongodi, T.
    role:
      role term: editor.
  name:
    name part: Balusamy, Balamurugan
    role:
      role term: editor.
  name:
    name part: Sharma, Meenakshi
    name part: (Lecturer in computer science)
    role:
      role term: editor.
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    date issued: 2022
    copyright date: 2023
    edition: First edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xii, 192 pages) : illustrations
  abstract: 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, facto…
  note: edited by P Suresh, T Poongodi, B Balamurugan, and Meenakshi Sharma.
  note: Includes bibliographical references and index.
  note: Prof. (Dr.) P Suresh is currently serving as Academic Coordinator and Professor in the Department of Mechanical Engineering at Galgotias University, Greater Noida. He received his Ph.D. degree in the Faculty of Mechanical Engineering, from Anna University, Tamilnadu, in 2014. He completed Master of Engineering in Engineering Design from Bharathiar University, Coimbatore, Tamilnadu in 2001 and a Bachelor of Engineering in University of Madras, Chennai, Tamilnadu in 2000. He has about 21 years of working experience in academics and research. He has published more than 55 publications in various International Journals, Conferences, and Book chapters in Elsevier, Springer, IET, etc. Dr. P. Suresh is also associated with various professional bodies such as The Institution of Engineers of India (IEI), IAENG, International Association of Engineers, Life member of ISTE (Indian Society for Technical Education), and he is the Senior Member of IRED. Prof. (Dr.) T Poongodi is a Professor in the Department of Computer Science and Engineering at the Galgotias University, Delhi - NCR, India. She received her Ph.D. degree in Information Technology (Information and Communication Engineering) from Anna University, Tamil Nadu, India. She has more than 15 years of experience working in teaching and research. Her current research interests include Network Security, Wireless Ad Hoc and Sensor Networks, Internet of Things (IoT), Computer Networks, and Blockchain Technology for emerging communication networks. Dr. T. Poongodi is the author of over 40+ book chapters including some reputed publishers such as Springer, Elsevier, Wiley, De-Gruyter, CRC Press, IGI global and 30+ international journals and conferences. She has published 10+ books in the areas of Internet of Things, Data Analytics, Blockchain Technology, Artificial Intelligence, Machine Learning, and Healthcare Informatics, published by reputed publishers such as Springer, IET, Wiley, CRC Taylor & Francis, and Apple Academic Pres…
  subject:
    topic: Manufacturing processes
    topic: Data processing
  subject:
    topic: Big data
  subject:
    topic: Machine learning
  subject:
    topic: Artificial intelligence
  subject:
    topic: Fabrication
    topic: Informatique
  subject:
    topic: Données volumineuses
  subject:
    topic: Apprentissage automatique
  subject:
    topic: Intelligence artificielle
  subject:
    topic: artificial intelligence
  subject:
    topic: COMPUTERS / Database Management / Data Mining
  subject:
    topic: TECHNOLOGY / Manufacturing
  subject:
    topic: Artificial intelligence
  subject:
    topic: Big data
  subject:
    topic: Machine learning
  subject:
    topic: Manufacturing processes
    topic: Data processing
  classification: TS183 .B54 2022
  classification: 670.285
  related item:
    title info:
      title: Big data analytics in smart manufacturing
    origin info:
      publisher: Boca Raton : Chapman & Hall/CRC Press, 2023
      edition: First edition.
    identifier: (DLC) 2022032387
  identifier: 9781003202776
  identifier: 1003202772
  identifier: 9781000815825
  identifier: 100081582X
  identifier: 9781000815740
  identifier: 1000815749
  identifier: 9781032065519
  identifier: 9781032065533
  identifier: 2022032388
  identifier: 9781003202776 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: DLC
    record creation date: 220707
    record change date: 20241108170026.3
    record identifier: in00005525991
    language of cataloging:
      language term: eng