Overview

This book collects perceptions and needs expectations and experiences concerning the application of Artificial Intelligence (AI) and Machine Learning in the steel sector. It contains a selection of themes discussed within the Workshop entitled “Impact and Opportunities of Artificial Intelligence in the Steel Industry” organized by the European Steel Technology Platform as an online event from October 15 until November 5, 2020. The event aimed at analyzing the diffusion of AI technologies in steelworks and at providing indications for future research, development and innovation actions addressing the sector demands. The chapters treat general analyses on transversal themes and applications for process optimization, product quality enhancement, yield increase, optimal exploitation of resources and smart data handling. The book is devoted to researchers and technicians in the steel or AI fields as well as for managers and policymakers exploring the opportunities provided by AI in industry.

Full Product Details

Author:   Valentina Colla ,  Costanzo Pietrosanti
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2021
Volume:   1338
Weight:   0.454kg
ISBN:  

9783030693664

ISBN 10:   303069366
Pages:   152
Publication Date:   05 February 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Challenges and frontiers in implementing artificial intelligence in process industry Marcus J. Neuer, Andreas Wolff, Norbert Holzknecht Data Pre-processing for effective design of Machine Learning-based models in the steel sector Silvia Cateni, Valentina Colla, Antonella Vignali, Marco Vannucci Quantifying uncertainty in physics-informed variational autoencoders for anomaly detection Marcus J. Neuer Mapping of Standardized State Machines to Utilize Machine Learning Models in Process Control Environments Julian Grothoff, Tobias Kleinert Quality4.0 - Transparent product quality supervision in the age of Industry 4.0 Jens Brandenburger, Christoph Schirm, Josef Melcher, Edgar Hancke, Marco Vannucci, Valentina Colla, Silvia Cateni, Rami Sellami, Sebastien Dupont, Annick Majchrowski, Asier Arteaga Artificial Intelligence and Machine Learning techniques for generation and assessment of products properties data Marco Vannucci, Valentina Colla, Antonio Ritacco, Marco Vannocci, Antonella Vignali The use of advanced data analytics to monitor process-induced changes to the microstructure and mechanical properties in flat steel strip Frenk Van Den Berg, Danique Fintelman, Haibing Yang, Claudio Mocci, Marco Vannucci, Valentina Colla Unsupervised Deep Learning for Detection of Non-uniform Surface Defect Distributions in Flat Steel Production Nicolas Camargo Torres, Jens Brandenburger Machine Learning-based models for supporting optimal exploitation of process off-gases in integrated steelworks Ismael Matino, Stefano Dettori, Angelo Castellano, Ruben Matino, Claudio Mocci, Marco Vannocci, Alessandro Maddaloni, Valentina Colla, Andreas Wolff Industrial Cyber Security at the Network Edge: the BRAINE Project approach Francesco Paolucci, Pavel Burget, Victor Genin, Ela Kolis, Gheorghe Dobra, Lucian Cotet, Irina Busila, Sylvain Guilley, Philippe Nguyen, Youssef Souissi, Liran Liss, Boris Pismeny, Juan Jose Vegas Olmos, Filippo Cugini Smart Steel Pipe Production Plant via Cognitive Digital Twins: A Case Study on Digitalization of Spiral Welded Pipe Machinery OEzlem Albayrak, Perin UEnal TSorage: A Modern and Resilient Platform for Time Series Management at Scale Mathieu Goeminne, Nico Salamone, Mohamed Boukhebouze, Stephane Mouton

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