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River Publishers Series in Communications 

Artificial Intelligence for Digitising Industry

Applications


Editors:
Ovidiu Vermesan, SINTEF, Norway
Reiner John, AVL List, Austria
Cristina De Luca, Infineon Technologies, Germany
Marcello Coppola, STMicroelectronics, France

ISBN: 9788770226646

e-ISBN: 9788770226639

doi: https://doi.org/10.13052/rp-9788770226639

Price: €0.00

Available: September 2021

Print book available at List Price

[198.43 MB] Downloads: [136] Reads [39]    

Description:

This book provides in-depth insights into use cases implementing artificial intelligence (AI) applications at the edge. It covers new ideas, concepts, research, and innovation to enable the development and deployment of AI, the industrial internet of things (IIoT), edge computing, and digital twin technologies in industrial environments. The work is based on the research results and activities of the AI4DI (ECSEL JU) project, including an overview of industrial use cases, research, technological innovation, validation, and deployment.

This book's sections build on the research, development, and innovative ideas elaborated for applications in five industries: automotive, semiconductor, industrial machinery, food and beverage, and transportation.

The articles included under each of these five industrial sectors discuss AI-based methods, techniques, models, algorithms, and supporting technologies, such as IIoT, edge computing, digital twins, collaborative robots, silicon-born AI circuit concepts, neuromorphic architectures, and augmented intelligence, that are anticipating the development of Industry 5.0.

Automotive applications cover use cases addressing AI-based solutions for inbound logistics and assembly process optimisation, autonomous reconfigurable battery systems, virtual AI training platforms for robot learning, autonomous mobile robotic agents, and predictive maintenance for machines on the level of a digital twin.

AI-based technologies and applications in the semiconductor manufacturing industry address use cases related to AI-based failure modes and effects analysis assistants, neural networks for predicting critical 3D dimensions in MEMS inertial sensors, machine vision systems developed in the wafer inspection production line, semiconductor wafer fault classifications, automatic inspection of scanning electron microscope cross-section images for technology verification, anomaly detection on wire bond process trace data, and optical inspection.

The use cases presented for machinery and industrial equipment industry applications cover topics related to wood machinery, with the perception of the surrounding environment and intelligent robot applications.

AI, IIoT, and robotics solutions are highlighted for the food and beverage industry, presenting use cases addressing novel AI-based environmental monitoring; autonomous environment-aware, quality control systems for Champagne production; and production process optimisation and predictive maintenance for soybeans manufacturing.

For the transportation sector, the use cases presented cover the mobility-as-a-service development of AI-based fleet management for supporting multimodal transport.

This book highlights the significant technological challenges that AI application developments in industrial sectors are facing, presenting several research challenges and open issues that should guide future development for evolution towards an environment-friendly Industry 5.0.

The challenges presented for AI-based applications in industrial environments include issues related to complexity, multidisciplinary and heterogeneity, convergence of AI with other technologies, energy consumption and efficiency, knowledge acquisition, reasoning with limited data, fusion of heterogeneous data, availability of reliable data sets, verification, validation, and testing for decision-making processes.

 


Keywords:

Artificial intelligence (AI), Industrial internet of things (IIoT), Machine learning, Deep learning, Neural Networks, Machine vision, Smart robots, AI at the edge, Silicon-born AI Industrial sectors: automotive, semiconductor, industrial machinery, food and beverage, transportation

Book Contents:

Preface

Artificial Intelligence for Digitising Industry – Applications

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Section 1

AI Automotive

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Chapter 1.0

AI Reshaping the Automotive Industry
by Daniel Plorin
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Chapter 1.1

AI for Inbound Logistics Optimisation in Automotive Industry
by Nikolaos Evangeliou, George Stamatis, George Bravos, Daniel Plorin and Dominik Stark
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Chapter 1.2

State of Health Estimation using a Temporal Convolutional Network for an Efficient Use of Retired Electric Vehicle Batteries within Second-Life Applications
by Steffen Bockrath, Stefan Waldhör, Harald Ludwig, Vincent Lorentz
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Chapter 1.3

Optimising Trajectories in Simulations with Deep Reinforcement Learning for Industrial Robots in Automotive Manufacturing
by Noah Klarmann, Mohammadhossein Malmir, Josip Josifovski, Daniel Plorin, MatthiasWagner and Alois C. Knoll
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Chapter 1.4

Foundations of Real Time Predictive Maintenance with Root Cause Analysis
by FranzWotawa, David Kaufmann, Adil Amukhtar, Iulia Nica, Florian Klück, Hermann Felbinger, Petr Blaha, Matus Kozovsky, Zdenek Havranek and Martin Dosedel
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Chapter 1.5

Real-Time Predictive Maintenance – Model-Based, Simulation-Based and Machine Learning Based Diagnosis
by FranzWotawa, David Kaufmann, Adil Amukhtar, Iulia Nica, Florian Klück, Hermann Felbinger, Petr Blaha, Matus Kozovsky, Zdenek Havranek and Martin Dosedel
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Chapter 1.6

Real-Time Predictive Maintenance – Artificial Neural Network Based Diagnosis
by Petr Blaha, Matus Kozovsky, Zdenek Havranek, Martin Dosedel, FranzWotawa, David Kaufmann, Adil Amukhtar, Iulia Nica, Florian Klück and Hermann Felbinger
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Section 2

AI Semiconductor

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Chapter 2.0

AI in Semiconductor Industry
by Cristina De Luca, Bernhard Lippmann, Wolfgang Schober, Saad Al-Baddai, Georg Pelz, Andreja Rojko, Frédéric Pétrot, Marcello Coppola and Reiner John
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Chapter 2.1

AI-Based Knowledge Management System for Risk Assessment and Root Cause Analysis in Semiconductor Industry
by Houssam Razouk, Roman Kern, Martin Mischitz, Josef Moser, Mirhad Memic, Lan Liu, Christian Burmer and Anna Safont-Andreu
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Chapter 2.2

Efficient Deep Learning Approach for Fault Detection in the Semiconductor Industry
by Liliana Andrade, Thomas Baumela, Frédéric Pétrot, David Briand, Olivier Bichler and Marcello Coppola
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Chapter 2.3

Towards Fully Automated Verification of Semiconductor Technologies
by Matthias Ludwig, Dinu Purice, Bernhard Lippmann, Ann-Christin Bette and Claus Lenz
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Chapter 2.4

Automated Anomaly Detection Through Assembly and Packaging Process
by Saad Al-Baddai, Martin Juhrisch, Jan Papadoudis, Anna Renner, Lippmann Bernhard, Cristina De Luca, Fabian Haas and Wolfgang Schober
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Section 3

AI Industrial Machinery

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Chapter 3.0

AI in Industrial Machinery
by Giulio Urlini, Janis Arents and Antonio Latella
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Chapter 3.1

AI-Powered Collision Avoidance Safety System for Industrial Woodworking Machinery
by Francesco Conti, Fabrizio Indirli, Antonio Latella, Francesco Papariello, Giacomo Michele Puglia, Felice Tecce, Giulio Urlini and Marcello Zanghieri
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Chapter 3.2

Construction of a Smart Vision-Guided Robot System for Manipulation in a Dynamic Environment
by Janis Arents, Modris Greitans and Bernd Lesser
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Chapter 3.3

Radar-Based Human-Robot Interfaces
by Hans Cappelle, Ali Gorji Daronkolaei, Ing Jyh Tsang, Björn Debaillie and Ilja Ocket
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Chapter 3.4

Touch Identification on Sensitive Robot Skin Using Time Domain Reflectometry and Machine Learning Methods
by Pawel Kostka, AnjaWinkler, Adnan Haidar, Muhammad Ghufran Khan, Rene Jäkel, PeterWinkler and Ralph Müller-Pfefferkorn
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Section 4

AI Food and Beverage

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Chapter 4.0

AI in Food and Beverage Industry
by Rachel Ouvinha de Oliveira, Marcello Coppola and Ovidiu Vermesan
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Chapter 4.1

Innovative Vineyards Environmental Monitoring System Using Deep Edge AI
by Marcello Coppola, Louis Noaille, Clément Pierlot, Rachel Ouvinha de Oliveira, Nathalie Gaveau, Marine Rondeau, Lucas Mohimont, Luiz Angelo Steffenel, Simone Sindaco and Tullio Salmon
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Chapter 4.2

AI-Driven Yield Estimation Using an Autonomous Robot for Data Acquisition
by Lucas Mohimont, Luiz Angelo Steffenel, Mathias Roesler, Nathalie Gaveau1, Marine Rondeau, François Alin, Clément Pierlot, Rachel Ouvinha de Oliveira and Marcello Coppola
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Chapter 4.3

AI-Based Quality Control System at the Pressing Stages of the Champagne Production
by Lucas Mohimont, Mathias Roesler, Angelo Steffenel, Nathalie Gaveau, Marine Rondeau, François Alin, Clément Pierlot, Rachel Ouvinha de Oliveira, Marcello Coppola and Philipe Doré
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Chapter 4.4

Optimisation of Soybean Manufacturing Process Using Real-time Artificial Intelligence of Things Technology
by Ovidiu Vermesan, Jøran Edell Martinsen, Anders Kristoffersen, Roy Bahr, Ronnie Otto Bellmann, Torgeir Hjertaker, John Breiland, Karl Andersen, Hans Erik Sand, Parsa Rahmanpour and David Lindberg
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Chapter 4.5

AI and IIoT-based Predictive Maintenance System for Soybean Processing
by Ovidiu Vermesan, Roy Bahr, Ronnie Otto Bellmann, Jøran Edell Martinsen, Anders Kristoffersen, Torgeir Hjertaker, John Breiland, Karl Andersen, Hans Erik Sand, Parsa Rahmanpour and David Lindberg
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Section 5

AI Transportation

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Chapter 5.0

Applications of AI in Transportation Industry
by Mathias Schneider, Matti Kutila and Alfred Höß
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Chapter 5.1

AI-Based Vehicle Systems for Mobility-as-a-Service Application
by Mikko Tarkiainen, Matti Kutila, Topi Miekkala, Sami Koskinen, Jokke Ruokolainen, Sami Dahlman and Jani Toiminen
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Chapter 5.2

Open Traffic Data for Mobility-as-a-Service Applications – Architecture and Challenges
by Mathias Schneider, Mina Marmpena, Haris Zafeiris, Ruben Prokscha, Seifeddine Saadani, Nikolaos Evangeliou, George Bravos and Alfred Höß
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Artificial Intelligence for Digitising Industry