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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
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 ApplicationsDownload as a PDF [185KB]
Section 1 AI AutomotiveDownload as a PDF [42KB]
Chapter 1.0 AI Reshaping the Automotive Industryby Daniel Plorin Download as a PDF [1744KB]
Chapter 1.1 AI for Inbound Logistics Optimisation in Automotive Industryby Nikolaos Evangeliou, George Stamatis, George Bravos, Daniel Plorin and Dominik Stark Download as a PDF [4738KB]
Chapter 1.2 State of Health Estimation using a Temporal Convolutional Network for an Efficient Use of Retired Electric Vehicle Batteries within Second-Life Applicationsby Steffen Bockrath, Stefan Waldhör, Harald Ludwig, Vincent Lorentz Download as a PDF [6252KB]
Chapter 1.3 Optimising Trajectories in Simulations with Deep Reinforcement Learning for Industrial Robots in Automotive Manufacturingby Noah Klarmann, Mohammadhossein Malmir, Josip Josifovski, Daniel Plorin, MatthiasWagner and Alois C. Knoll Download as a PDF [33085KB]
Chapter 1.4 Foundations of Real Time Predictive Maintenance with Root Cause Analysisby FranzWotawa, David Kaufmann, Adil Amukhtar, Iulia Nica, Florian Klück, Hermann Felbinger, Petr Blaha, Matus Kozovsky, Zdenek Havranek and Martin Dosedel Download as a PDF [3835KB]
Chapter 1.5 Real-Time Predictive Maintenance – Model-Based, Simulation-Based and Machine Learning Based Diagnosisby FranzWotawa, David Kaufmann, Adil Amukhtar, Iulia Nica, Florian Klück, Hermann Felbinger, Petr Blaha, Matus Kozovsky, Zdenek Havranek and Martin Dosedel Download as a PDF [6286KB]
Chapter 1.6 Real-Time Predictive Maintenance - Artificial Neural Network Based Diagnosisby Petr Blaha, Matus Kozovsky, Zdenek Havranek, Martin Dosedel, FranzWotawa, David Kaufmann, Adil Amukhtar, Iulia Nica, Florian Klück and Hermann Felbinger Download as a PDF [9267KB]
Section 2 AI SemiconductorDownload as a PDF [42KB]
Chapter 2.0 AI in Semiconductor Industryby Cristina De Luca, Bernhard Lippmann, Wolfgang Schober, Saad Al-Baddai, Georg Pelz, Andreja Rojko, Frédéric Pétrot, Marcello Coppola and Reiner John Download as a PDF [106KB]
Chapter 2.1 AI-Based Knowledge Management System for Risk Assessment and Root Cause Analysis in Semiconductor Industryby Houssam Razouk, Roman Kern, Martin Mischitz, Josef Moser, Mirhad Memic, Lan Liu, Christian Burmer and Anna Safont-Andreu Download as a PDF [6243KB]
Chapter 2.2 Efficient Deep Learning Approach for Fault Detection in the Semiconductor Industryby Liliana Andrade, Thomas Baumela, Frédéric Pétrot, David Briand, Olivier Bichler and Marcello Coppola Download as a PDF [18163KB]
Chapter 2.3 Towards Fully Automated Verification of Semiconductor Technologiesby Matthias Ludwig, Dinu Purice, Bernhard Lippmann, Ann-Christin Bette and Claus Lenz Download as a PDF [9530KB]
Chapter 2.4 Automated Anomaly Detection Through Assembly and Packaging Processby Saad Al-Baddai, Martin Juhrisch, Jan Papadoudis, Anna Renner, Lippmann Bernhard, Cristina De Luca, Fabian Haas and Wolfgang Schober Download as a PDF [10214KB]
Section 3 AI Industrial MachineryDownload as a PDF [42KB]
Chapter 3.0 AI in Industrial Machineryby Giulio Urlini, Janis Arents and Antonio Latella Download as a PDF [103KB]
Chapter 3.1 AI-Powered Collision Avoidance Safety System for Industrial Woodworking Machineryby Francesco Conti, Fabrizio Indirli, Antonio Latella, Francesco Papariello, Giacomo Michele Puglia, Felice Tecce, Giulio Urlini and Marcello Zanghieri Download as a PDF [4530KB]
Chapter 3.2 Construction of a Smart Vision-Guided Robot System for Manipulation in a Dynamic Environmentby Janis Arents, Modris Greitans and Bernd Lesser Download as a PDF [6437KB]
Chapter 3.3 Radar-Based Human-Robot Interfacesby Hans Cappelle, Ali Gorji Daronkolaei, Ing Jyh Tsang, Björn Debaillie and Ilja Ocket Download as a PDF [10868KB]
Chapter 3.4 Touch Identification on Sensitive Robot Skin Using Time Domain Reflectometry and Machine Learning Methodsby Pawel Kostka, AnjaWinkler, Adnan Haidar, Muhammad Ghufran Khan, Rene Jäkel, PeterWinkler and Ralph Müller-Pfefferkorn Download as a PDF [4532KB]
Section 4 AI Food and BeverageDownload as a PDF [42KB]
Chapter 4.0 AI in Food and Beverage Industryby Rachel Ouvinha de Oliveira, Marcello Coppola and Ovidiu Vermesan Download as a PDF [108KB]
Chapter 4.1 Innovative Vineyards Environmental Monitoring System Using Deep Edge AIby Marcello Coppola, Louis Noaille, Clément Pierlot, Rachel Ouvinha de Oliveira, Nathalie Gaveau, Marine Rondeau, Lucas Mohimont, Luiz Angelo Steffenel, Simone Sindaco and Tullio Salmon Download as a PDF [3332KB]
Chapter 4.2 AI-Driven Yield Estimation Using an Autonomous Robot for Data Acquisitionby Lucas Mohimont, Luiz Angelo Steffenel, Mathias Roesler, Nathalie Gaveau1, Marine Rondeau, François Alin, Clément Pierlot, Rachel Ouvinha de Oliveira and Marcello Coppola Download as a PDF [8537KB]
Chapter 4.3 AI-Based Quality Control System at the Pressing Stages of the Champagne Productionby Lucas Mohimont, Mathias Roesler, Angelo Steffenel, Nathalie Gaveau, Marine Rondeau, François Alin, Clément Pierlot, Rachel Ouvinha de Oliveira, Marcello Coppola and Philipe Doré Download as a PDF [4112KB]
Chapter 4.4 Optimisation of Soybean Manufacturing Process Using Real-time Artificial Intelligence of Things Technologyby 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 Download as a PDF [14239KB]
Chapter 4.5 AI and IIoT-based Predictive Maintenance System for Soybean Processingby 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 Download as a PDF [11853KB]
Section 5 AI TransportationDownload as a PDF [42KB]
Chapter 5.0 Applications of AI in Transportation Industryby Mathias Schneider, Matti Kutila and Alfred Höß Download as a PDF [2455KB]
Chapter 5.1 AI-Based Vehicle Systems for Mobility-as-a-Service Applicationby Mikko Tarkiainen, Matti Kutila, Topi Miekkala, Sami Koskinen, Jokke Ruokolainen, Sami Dahlman and Jani Toiminen Download as a PDF [10872KB]
Chapter 5.2 Open Traffic Data for Mobility-as-a-Service Applications - Architecture and Challengesby Mathias Schneider, Mina Marmpena, Haris Zafeiris, Ruben Prokscha, Seifeddine Saadani, Nikolaos Evangeliou, George Bravos and Alfred Höß Download as a PDF [9316KB]