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Big data analytics in smart manufacturing
1 online resource (xii, 192 pages) : illustrations
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
edited by P Suresh, T Poongodi, B Balamurugan, and Meenakshi Sharma.
Includes bibliographical references and index.
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 Press. Prof. (Dr.) B Balamurugan is currently working as Associate Dean-Student Engagement, Shiv Nadar University, Delhi-National Capital Region (NCR), India. His contributions focus on Engineering Education, Blockchain, and Data Sciences. His Academic degrees and twelve years of experience working as a faculty in a global University like VIT University, Vellore have made him more receptive and prominent in his domain. He does have 200 plus high impact factor papers in Springer, Elsevier, and IEEE. He has done more than 50 Edited and authored books and collaborated with eminent professors across the world from top QS ranked universities. Prof. Balamurugan Balusamy has served up to the position of Associate Professor in his stint of 12 years of experience with VIT University, Vellore. He had completed his Bachelors, Master and PhD Degrees from Top premier institutions in India. His passion is teaching and adapting different design thinking principles while delivering his lectures. He has published 30+ books on various technologies and visited 15 plus countries for his technical course. He has several top-notch conferences in his resume and has published over 200 quality journal, conferences and book chapters combined. He serves on the advisory committee for several start-ups and forums and does consultancy work for the industry on Industrial IoT. He has given over 175 talks at various events and symposiums. He is currently working as a professor and chief research coordinator at Galgotias University and teaches faculty and students about research, does research on Blockchain and IoT. Dr. Meenakshi Sharma, Professor Dean R&D in Galgotias University, Greater Noida. M.Tech in Computer Science and Engineering from Kurukshetra University in 2006. She has been awarded Ph.D. in Computer Science, from Kurukshetra University in 2011. She has 15+ Years of Experience in Teaching and Research. Her research interests are Machine Learning, Image Processing, Big Data Analytics, Data compression, and Digital and data warehousing. She has a total of 50+ Research publications in IEEE transaction, SCIE, SCI, and Scopus. She got the Best Research and Teacher award in 2017 and 2018. She attended as Session Chair in Many International Conferences and gave Guest Lecturer on Machine Learning, and Big Data in Many Engineering Colleges. She works as a Reviewer in many SCI and Scopus Indexed Journals. She is the GUEST editor (SCOPUS JOURNAL). She is also Guest Editor, (CRC Press) Taylor Francis. She had guided 02 Ph.D. Candidate, 01 Thesis Submitted, and 05 are under Guidance.
COMPUTERS / Database Management / Data Mining
Boca Raton : Chapman & Hall/CRC Press, 2023