- Inbunden (Hardback)
- Antal sidor
- 1st ed. 2020
- Springer Nature Switzerland AG
- Patnaik, Srikanta (ed.)
- 100 Tables, color; XI, 180 p.
- 234 x 156 x 13 mm
- Antal komponenter
- 1 Hardback
- 449 g
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New Paradigm of Industry 4.0
Internet of Things, Big Data & Cyber Physical Systems1819Skickas inom 10-15 vardagar.
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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.
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"I would recommend this book primarily for those who are working in disaster management and who are geospatial information specialists in disaster management. ... The book can also be important for those working on filling the skill gap caused by Industry 4.0, for they can get a broader overview of relevant applications." (Abdelkarim Alhloul, Hungarian Geographical Bulletin, Vol. 69 (2), 2020)
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.