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Digital Transformation: Core Technologies and Emerging Topics from a Computer Science PerspectiveНазвание: Digital Transformation: Core Technologies and Emerging Topics from a Computer Science Perspective
Автор: Birgit Vogel-Heuser, Manuel Wimmer
Издательство: Springer
Год: 2023
Страниц: 522
Язык: английский
Формат: pdf (true)
Размер: 12.6 MB

Digital Transformation in Industry 4.0/5.0 requires the effective and efficient application of digitalization technologies in the area of production systems. This book elaborates on concepts, techniques, and technologies from computer science in the context of Industry 4.0/5.0 and demonstrates their possible applications. Thus, the book serves as an orientation but also as a reference work for experts in the field of Industry 4.0/5.0 to successfully advance digitization in their companies.

The book “Digital Transformation: Core Technologies and Emerging Topics from a Computer Science Perspective” is structured into five parts. While Part 1 is about why and how industrial systems are represented as digital artefacts, Part 2 is focussing on emerging digital infrastructures to run industrial systems by showing their potential and applications, as well as how they can be integrated and secured in larger settings. Parts 3 and 4 are focusing on the data-driven paradigm, especially on data management and analytics which opens the door for a multitude of innovation potentials for industrial systems. Finally, Part 5 is giving an outlook on particular digital transformations aspects such as improved human-machine interactions possibilities as well as driving and managing organizational issues such as enterprise model transformations. By this, the book gives an outlook on the emerging Industry 5.0 paradigm.

Contents:
Part I. Digital Representation
Engineering Digital Twins and Digital Shadows as Key Enablers for Industry 4.0
Designing Strongly-decoupled Industry 4.0 Applications Across the Stack: A Use Case
Variability in Products and Production
Part II. Digital Infrastructures
Part III. Data Management
Big Data Integration for Industry 4.0
Massive Data Sets – Is Data Quality Still an Issue?
Modelling the Top Floor: Internal and External Data Integration and Exchange
Part IV. Data Analytics
Part V. Digital Transformation towards Industry 5.0

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