Ontology-Based Development of Industry 4.0 and 5.0 Solutions for Smart Manufacturing and Production / Springer Series in Advanced Manufacturing (PDF)
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The book provides an extensive overview of semantic technologies and their potential to integrate with existing industrial standards, planning, and execution systems to provide efficient data processing and analysis. It also investigates the design of Industry 5.0 solutions and the need for problem-specific descriptions of production processes, operator skills and states, and sensor monitoring in intelligent spaces.
The book proposes that ontology-based data can efficiently represent enterprise and manufacturing datasets.
The book is divided into two parts: modelingand optimization. The semantic modeling part provides an overview of ontologies and knowledge graphs that can be used to create Industry 4.0 and 5.0 applications, with two detailed applications presented on a reproducible industrial case study. The optimization part of the book focuses on network science-based process optimization and presents various detailed applications, such as graph-based analytics, assembly line balancing, and community detection.
The book is based on six key points: the need for horizontal and vertical integration in modern industry; the potential benefits of integrating semantic technologies into ERP and MES systems; the importance of optimization methods in Industry 4.0 and 5.0 concepts; the need to process large amounts of data while ensuring interoperability and re-usability factors; the potential for digital twin models to model smart factories, including big data access; and the need to integrate human factors in CPSs and provide adequate methods tofacilitate collaboration and support shop floor workers.
Tamas Ruppert is an Associate Professor at the Department of Process Engineering at the University of Pannonia, with a focus oncomputer science. He graduated with bachelor's degrees in Mechanical Engineering and Engineering Information Technology in 2015, and a master's degree in Mechatronic Engineering in 2016. He received his PhD degree in 2020. His research interests cover activity recognition, discrete-event simulators, human-centric solutions, and Operator 4.0.
Laszlo Nagy received the bachelor's degree in mechatronics engineering in 2015, the master's degree in mechatronics engineering, in 2017, and the Ph.D. degree, in 2023.
He has five years of experience as an Instrumentation and Controls Field Service Engineer at Siemens, working with industrial gas turbines worldwide.
His research interest covers the areas of semantic networks, modeling of manufacturing systems, and development of complex optimization methods. Furthermore, study the industry 5.0, human-centered approach, using knowledge graphs and ontologies.
- Autoren: János Abonyi , László Nagy , Tamás Ruppert
- 2024, 1st ed. 2024, 271 Seiten, Englisch
- Verlag: Springer International Publishing
- ISBN-10: 3031474449
- ISBN-13: 9783031474446
- Erscheinungsdatum: 01.01.2024
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- Dateiformat: PDF
- Grösse: 11 MB
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