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Artificial Intelligence in Industry 4.0

A Collection of Innovative Research Case-studies that are Reworking the Way We Look at Industry 4.0 Thanks to Artificial Intelligence

  • Book
  • © 2021

Overview

Editors:
  1. Alexiei Dingli

    1. Faculty of ICT, Department of Artificial Intelligence, University of Malta, Msida, Malta

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  2. Foaad Haddod

    1. Faculty of ICT, Department of Artificial Intelligence, University of Malta, Msida, Malta

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    You can also search for this editor in PubMed   Google Scholar

  3. Christina Klüver

    1. Universität Duisburg-Essen, Essen, Germany

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    You can also search for this editor in PubMed   Google Scholar

  • Presents a wide range of innovative research case studies of Artificial Intelligence in Industry 4.0
  • Explores different solutions brought forth by AI pushing forward Industry 4.0
  • Written by experts in the field

Part of the book series: Studies in Computational Intelligence (SCI, volume 928)

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-xxv
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  2. Managing the Industry 4.0 Revolution

    1. Front Matter

      Pages 1-1
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    2. Implementing Industry 4.0—The Need for a Holistic Approach

      • Christian Hoyer, Indra Gunawan, Carmen Haule Reaiche
      Pages 3-14

    3. Motivation in a Business Company Using Technology-Based Communication

      • Madara Pratt, Sarma Cakula
      Pages 15-30

    4. Decision Support in Everyday Business Using Self-enforcing Networks

      • Christina Klüver, Jürgen Klüver
      Pages 31-44

    5. Approaches for Cognitive Assistance in Industry 4.0 Assembly

      • Thomas Schack, Benjamin Strenge, Kai Essig
      Pages 45-54

  3. Modelling for Industry 4.0

    1. Front Matter

      Pages 55-55
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    2. Modelling and Simulation in Industry 4.0

      • William de Paula Ferreira, Fabiano Armellini, Luis Antonio de Santa-Eulalia, Claudia Rebolledo
      Pages 57-72

    3. Homogenization Algorithm Based on Incremental L2-Discrepancy Filtering for Data-Driven Modelling

      • Zhuang Shao, Fengqi Si, Zhigao Xu, Ding Guo
      Pages 73-83

    4. Linking Industry 4.0, Learning Factory and Simulation: Testbeds and Proof-of-Concept Experiments

      • William de Paula Ferreira, Arun Palaniappan, Fabiano Armellini, Luis Antonio de Santa-Eulalia, Elaine Mosconi, Guillaume Marion
      Pages 85-96

  4. Machine Learning in Industry 4.0

    1. Front Matter

      Pages 97-97
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    2. Intelligent Digital Twin System in the Semiconductors Manufacturing Industry

      • Foaad Haddod, Alexiei Dingli
      Pages 99-113

    3. Automatic Defect Recognition  in Nonwovens Using Images and Metadata Analysis—A Deep Learning  Approach

      • Marco Calderisi, Gabriele Galatolo, Ilaria Ceppa, Tommaso Motta, Francesco Vergentini
      Pages 115-126

    4. MIRAI: A Modifiable, Interpretable, and Rational AI Decision Support  System

      • Natalia Mallia, Alexiei Dingli, Foaad Haddod
      Pages 127-141

    5. Multi-Agent Reinforcement Learning for the Energy Optimization of Cyber-Physical Production Systems

      • Jupiter Bakakeu, Schirin Baer, Hans-Henning Klos, Joern Peschke, Matthias Brossog, Joerg Franke
      Pages 143-163

    6. Affect of Artificial Intelligence  Technologies and Digitalisation on Jurisprudence and Education

      • Tatiana V. Emelianova
      Pages 165-179

  5. Agents in Industry 4.0

    1. Front Matter

      Pages 181-181
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    2. Approach for Model Driven  Development of Multi- agent  Systems for Ambient Intelligence

      • Tsvetelina Ivanova, Idilia Batchkova
      Pages 183-198

    3. Designing Trust in Highly Automated  Virtual Assistants : A Taxonomy of Levels of Autonomy

      • Fernando Galdon, Ashley Hall, Stephen Jia Wang
      Pages 199-211

    4. Introducing the Concept of “Digital-Agent Signatures ”: How SSI Can Be Expanded for the Needs of Industry 4.0.

      • Alexander Pfeiffer, Mark Bugeja
      Pages 213-233
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Keywords

About this book

This book is intended to help management and other interested parties such as engineers, to understand the state of the art when it comes to the intersection between AI and Industry 4.0 and get them to realise the huge possibilities which can be unleashed by the intersection of these two fields. We have heard a lot about Industry 4.0, but most of the time, it focuses mainly on automation. In this book, the authors are going a step further by exploring advanced applications of Artificial Intelligence (AI) techniques, ranging from the use of deep learning algorithms in order to make predictions, up to an implementation of a full-blown Digital Triplet system. The scope of the book is to showcase what is currently brewing in the labs with the hope of migrating these technologies towards the factory floors. Chairpersons and CEOs must read these papers if they want to stay at the forefront of the game, ahead of their competition, while also saving huge sums of money in the process.

Editors and Affiliations

  • Faculty of ICT, Department of Artificial Intelligence, University of Malta, Msida, Malta

    Alexiei Dingli, Foaad Haddod

  • Universität Duisburg-Essen, Essen, Germany

    Christina Klüver

Bibliographic Information

  • Book Title: Artificial Intelligence in Industry 4.0

  • Book Subtitle: A Collection of Innovative Research Case-studies that are Reworking the Way We Look at Industry 4.0 Thanks to Artificial Intelligence

  • Editors: Alexiei Dingli, Foaad Haddod, Christina Klüver

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-030-61045-6

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: Springer Nature Switzerland AG 2021

  • Hardcover ISBN: 978-3-030-61044-9Published: 28 February 2021

  • Softcover ISBN: 978-3-030-61047-0Published: 01 March 2022

  • eBook ISBN: 978-3-030-61045-6Published: 27 February 2021

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XXV, 236

  • Number of Illustrations: 13 b/w illustrations, 52 illustrations in colour

  • Topics: Computational Intelligence, Industrial and Production Engineering

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