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Authorized users
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Can lend chapters, not whole ebooks
Title
New paradigm of industry 4.0 : Internet of things, big data & cyber physical systems / Srikanta Patnaik, editor.
ISBN
9783030257781 (electronic book)
3030257789 (electronic book)
9783030257774
Published
Cham : Springer, [2020]
Copyright
©2020
Language
English
Description
1 online resource.
Item Number
10.1007/978-3-030-25778-1 doi
Call Number
HD2326 .N48 2020eb
Dewey Decimal Classification
338.6
Summary
The book provides readers with an overview of the state of the art in the field of Industry 4.0 and related research advancements. The respective chapters identify and discuss new dimensions of both risk factors and success factors, along with performance metrics that can be employed in future research work. They also discuss a number of real-time issues, problems and applications with corresponding solutions and suggestions. Sharing new theoretical findings, tools and techniques for Industry 4.0, and covering both theoretical and application-oriented approaches, the book offers a valuable asset for newcomers to the field and practicing professionals alike.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed September 13, 2019).
Series
Studies in big data ; v. 64.
Management of V.U.C.A. (Volatility, Uncertainty, Complexity and Ambiguity) using Machine Learning Techniques in Industry 4.0 Paradigm.- Role of Industry 4.0 in Performance Improvement of Furniture Cluster.- Imparting Industry 4.0 Education using Open Source Tools: A Case.- Decision support framework for smart implementation of green supply chain management practices.- Decision Support System for Supply Chain Performance Measurement: Case of Textile Industry.- On the Condition Monitoring and Maintenance Approaches for Corrosive Sulphur Deposition in Oil-Filled Electrical Transformers.- Principal Components based Multivariate Statistical Process Monitoring of Machining Process using Machine Vision Approach.- Green IS
Exploring Environmental Sensitive IS through the Lens of Enterprise Architecture.
