{"id":252257,"date":"2026-07-13T01:54:50","date_gmt":"2026-07-12T22:54:50","guid":{"rendered":"https:\/\/1kitap1.com\/en\/artificial-intelligence-data-and-robotics-edward-curry\/"},"modified":"2026-07-13T01:54:50","modified_gmt":"2026-07-12T22:54:50","slug":"artificial-intelligence-data-and-robotics-edward-curry","status":"publish","type":"post","link":"https:\/\/1kitap1.com\/en\/artificial-intelligence-data-and-robotics-edward-curry\/","title":{"rendered":"Artificial Intelligence Data And Robotics – Edward Curry"},"content":{"rendered":"
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Continuous cloud collection of laser-cutter status data from customer- owned machines will support anomaly detection. Having maintenance sessions scheduled in advance reduces inventory stocks by relying more on just-in-time replacement parts delivery by suppliers. Milling Machine Usage Data Sharing: Milling machine monitoring data from will be shared sharing between the OEM, the machine owners\/users, and parts suppliers. The OEM will be able to offer pre- scheduled maintenance operations. Based on part-failure data, parts manufacturers will be able to improve their designs for durability, and end users will benefit from usage analytics and minimized unplanned downtimes.<\/p>\n

SM4RTENANCE seeks to bolster intelligent asset management and predictive maintenance through the implementation of data space technology. The project advances data interoperability and compliance across multiple industries, driving efficiency, sustainability, and resilience in industrial maintenance and operations. Federation efforts push the current boundaries of data space technology and seek to even further tear down data-silos walls and maximize the value of industrial data. 3.1.3 RE4DY Project: European Data as a PRoduct Value Ecosystems for Resilient Factory 4.0 Product and ProDuction ContinuitY and Sustainability The RE4DY project is not only creating a groundbreaking platform for industrial decision-making but also providing businesses with the tools they need to implement it.<\/p>\n

Grounded in the Manufacturing Data Networks vision, RE4DY prioritizes \u201cData as a Product\u201d and empowers businesses to develop, share, and utilize data securely and efficiently [12]. The key to this platform is a digital continuum that seamlessly connects every stage of the manufacturing process, from design and production to maintenance and end-of-life management.<\/p>\n

This comprehensive approach, combined with AI and advanced data exploitation, empowers businesses to optimize operations, enhance competitiveness, and embrace the core principles of Industry 5.0. RE4DY recognizes the urgent need for data-driven digital manufacturing processes to incorporate innovative and active resiliency strategies at both production and supply chain levels [13]. This is crucial for European manufacturers to maintain their sovereignty and competitiveness while upholding European digital values such as excellence, privacy, and trust.<\/p>\n

The project aims to demonstrate that the European industry can jointly build unique data-driven digital value networks 4.0 to sustain competitive advantages through digital continuity and sovereign data spaces. By establishing a \u201cData as a Product\u201d core concept, RE4DY facilitates the implementation of digital continuity across digital threads, data spaces, digital twin workflows, and AI\/ML\/Data pipelines. This concept leverages resiliency on top of advanced manufacturing digital processes and value ecosystems, supporting the development and implementation of digital continuity.<\/p>\n

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This work was supported by the University of Galway. \u00a9 The Editor(s) (if applicable) and The Author(s) 2026. This book is an open access publication. Open Access This book is licensed under the terms of the Creative Commons Attribution 4.0 International License (http:\/\/\u200bcreativecommons.\u200b org\/\u200blicenses\/\u200bby\/\u200b4.\u200b0\/\u200b), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.<\/p>\n

The images or other third party material in this book are included in the book’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the book’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.<\/p>\n

The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication.<\/p>\n

Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland 1kitap1.com\/en Preface The most transformative technologies in human history have been those that have fundamentally reshaped societies, economies, and human capabilities.<\/p>\n

Agriculture enabled permanent human settlements and the rise of civilizations, writing systems facilitated record-keeping and cultural transmission, and electricity revolutionized industry and communication. Today, the convergence of artificial intelligence, data, and robotics (ADR) technology marks a significant step change, with the potential to transform society. It offers opportunities to automate cognition and physical interaction, as well as to foster new forms of creativity and decision- making. However, it also presents challenges in translating core ADR strengths into advances in industrial competitiveness, societal well-being, and environmental sustainability. The aim of this book is to educate readers about techniques and technologies related to AI, data, and robotics.<\/p>\n

It explores cutting-edge theories, tools, methodologies, and best practices within the context of both industrial and public sector scenarios.<\/p>\n<\/blockquote>\n

This is a short excerpt from the opening of “” by Unknown, quoted for review and introduction purposes. All rights belong to the copyright holders.<\/em><\/p>\n

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