| Autor: |
Oscar Lázaro, Jesús Alonso, Roxana-Maria Holom, Katharina Rafetseder, Stefanie Kritzinger, Fernando Ubis, Gerald Fritz, Alois Wiesinger, Harald Sehrschön, Jimmy Nguyen, Tomasz Luniewski, Wojciech Zietak, Jerome Clavel, Roberto Perez, Marlene Hildebrand, Dimitris Kiritsis, Hugues-Arthur Garious, Silvia de la Maza, Antonio Ventura-Traveset, Juanjo Hierro, Gernot Boege, Ulrich Ahle |
| Rok vydání: |
2022 |
| Zdroj: |
Technologies and Applications for Big Data Value ISBN: 9783030783068 |
| DOI: |
10.1007/978-3-030-78307-5_18 |
| Popis: |
With the rising complexity of modern products and a trend from single products to Systems of Systems (SoS) where the produced system consists of multiple subsystems and the integration of multiple domains is a mandatory step, new approaches for development are demanded. This chapter explores how Model-Based Systems Engineering (MBSE) can benefit from big data technologies to implement smarter engineering processes. The chapter presents the Boost 4.0 Testbed that demonstrates how digital twin continuity and digital thread can be realized from service engineering, production, product performance, to behavior monitoring. The Boost 4.0 testbed demonstrates the technical feasibility of an interconnected operation of digital twin design, ZDM subtractive manufacturing, IoT product monitoring, and spare part 3D printing services. It shows how the IDSA reference model for data sovereignty, blockchain technologies, and FIWARE open-source technology can be jointly used for breaking silos, providing a seamless and controlled exchange of data across digital twins based on open international standards (ProStep, QIF), allowing companies to dramatically improve cost, quality, timeliness, and business results. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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