Big Data Analytics in Smart Manufacturing Principles and Practices PDF

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.

Authors: P Suresh, T Poongodi, B Balamurugan, Meenakshi Sharma