514
517 515
518 516
519 517
520 518
521 519
522 520
Electronics in Advanced Research Industries
Industry 4.0 to Industry 5.0 Advances
Alessandro Massaro
This edition first published 2022
© 2022 John Wiley & Sons Ltd
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.
The right of Alessandro Massaro to be identified as the author of this work has been asserted in accordance with law.
Registered Offices John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK
Editorial Office The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK
For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com.
Wiley also publishes its books in a variety of electronic formats and by print‐on‐demand. Some content that appears in standard print versions of this book may not be available in other formats.
Limit of Liability/Disclaimer of Warranty While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.
Library of Congress Cataloging‐in‐Publication Data
Names: Massaro, Alessandro, 1974– author.
Title: Electronics in advanced research industries : industry 4.0 to industry 5.0 advances / Alessandro Massaro, Dyrecta Lab, Research Institute, Conversano (Ba), Italy.
Description: Hoboken, NJ, USA : Wiley, 2022. | Includes bibliographical references and index.
Identifiers: LCCN 2021028944 (print) | LCCN 2021028945 (ebook) | ISBN 9781119716877 (hardback) | ISBN 9781119716884 (adobe pdf) | ISBN 9781119716891 (epub)
Subjects: LCSH: Industry 4.0. | Automation.
Classification: LCC T59.6 .M37 2022 (print) | LCC T59.6 (ebook) | DDC 658.4/038028563–dc23
LC record available at https://lccn.loc.gov/2021028944 LC ebook record available at https://lccn.loc.gov/2021028945
Cover Design: Wiley
Cover Image: © raigvi/Shutterstock
To my family: Magda, Andrea, Adriano, and Peggy
Preface
Modern technologies in production systems open new approaches and concepts of industrial production. The digital Industry 4.0 upgrade provides new elements to control and manage production in all industry sectors. This upgrade allows to improve product quality, and in general the whole supply chain. The new digital technologies include hardware and software tools integrated in infrastructure oriented on the gain of digital knowledge. The fast dynamicity of the markets, the increase of the global competition between companies, and the unpredictable social and health events, imposes the need to think of a new concept of a production system based on full automatisms and self‐adaptive processes, predicting production failures and product defects. In this context, the Industry 4.0 facilities can be furthermore upscaled to an intelligent control and actuation system of the production, characterizing the new Industry 5.0 scenario. The new facilities which contribute to Industry 5.0 passage are mainly based on artificial intelligence (AI) implementations in production and information systems, accomplishing predictive maintenance, failure prediction, defect classification, efficient robotic control and actuation, design optimization, testing improvements, and in general technological advances due to the possibility to quickly process data in each production stage. This book analyzes innovative production approaches, and the integration aspects of the AI in different industrial digital technologies, by enhancing specific functionalities. In innovative production systems, AI is fully integrated in information systems and covers cybersecurity, quality processes, business intelligence and intelligent production management. The innovative production is also related to new services associated with the introduction in the market of new technologies such as for the telemedicine sector, and in general for industrial diagnostics, where AI is also adopted for the improvement of inspection services. The main advantage of AI is the self‐learning of the algorithms able to learn automatically from the same production data of companies. In an industrial upgrade, the implementation of sensor control and actuation based on intelligent feedback systems is especially important. In this scenario, AI algorithms can accomplish robotic movement, by automatically optimizing the machine parameter setting, by means of image and data processing. The correct use of AI is mainly based on the formulation of the algorithm, and on the dataset adopted to learn the related model. For each application there is an associated AI learning dataset which can be improved by big data systems. In particular, image processing and image segmentation approaches can be improved by AI, enhancing hidden information
