Big Data Analytics in Smart Manufacturing: Principles and Practices

[LeeAndro]

English | 2022 | ISBN: ‎ 978-1032065519 | 205 pages | True PDF | 9.67 MB

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, muldia 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 emeg 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.
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