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AI Factory: Theories, Applications and Case Studies
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-0055-2740
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-4107-0991
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0001-8111-6918
2023 (English)Book (Other academic)
Abstract [en]

This book provides insights into how to approach and utilise data science tools, technologies, and methodologies related to artificial intelligence (AI) in industrial contexts. It explains the essence of distributed computing and AI technologies and their interconnections. It includes descriptions of various technology and methodology approaches and their purpose and benefits when developing AI solutions in industrial contexts. In addition, this book summarises experiences from AI technology deployment projects from several industrial sectors. Features:

• Presents a compendium of methodologies and technologies in industrial AI and digitalisation.

• Illustrates the sensor-to-actuation approach showing the complete cycle, which defines and differentiates AI and digitalisation.

• Covers a broad range of academic and industrial issues within the field of asset management.

• Discusses the impact of Industry 4.0 in other sectors.

• Includes a dedicated chapter on real-time case studies.

This book is aimed at researchers and professionals in industrial and software engineering, network security, AI and machine learning (ML), engineering managers, operational and maintenance specialists, asset managers, and digital and AI manufacturing specialists.

Place, publisher, year, edition, pages
Taylor & Francis, 2023, 1. , p. 444
Series
AI Factory: Theories, Applications and Case Studies
National Category
Computer Systems
Research subject
Operation and Maintenance Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-99496DOI: 10.1201/9781003208686Scopus ID: 2-s2.0-85165345291ISBN: 9781032077642 (print)ISBN: 9781003208686 (electronic)OAI: oai:DiVA.org:ltu-99496DiVA, id: diva2:1787130
Available from: 2023-08-11 Created: 2023-08-11 Last updated: 2023-08-11Bibliographically approved

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Karim, RaminGalar, DiegoKumar, Uday

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