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Record Nr. |
UNINA9910847595903321 |
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Autore |
Blaschke Florian |
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Titolo |
Implementation and Benefits of Digital Twin on Decision Making and Data Quality Management / / by Florian Blaschke |
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Pubbl/distr/stampa |
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Wiesbaden : , : Springer Fachmedien Wiesbaden : , : Imprint : Springer Gabler, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (188 pages) |
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Disciplina |
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Soggetti |
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Business information services |
IT in Business |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Introduction -- Literature Review -- Objectives -- Materials And Methods Of Dissertation -- Results And Evaluation -- Conclusions And Recommendations -- New Scientific Results. |
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Sommario/riassunto |
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Digital twin technology is becoming important for the realization of Industry 4.0 using cyber-physical systems (CPS) and information technology. CPS form the backbone to support the creation of a network for decentralized and autonomous decision-making. The design principles for Industry 4.0 serve as guidelines for virtualization concepts that are virtual copies of the physical world and create a link between the real and virtual worlds to collect data and monitor processes, the so-called digital twin. In this book, a theoretical digital twin-driven decision-making model has been developed that combines corporate data quality management, a process digital twin, and a model-driven decision support system. It leverages the benefits of the digital twin to create, test and build a process in the virtual world that supports decision making by combining data, analytics and visualization of insights to help managers make better decisions About the author Dr. Florian Blaschke gained practical experience as a project coordinator in vehicle development for quality-assured product data management and the digital twin, as well as leading a controlling team in a retail company to ensure and improve the data quality of key |
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figures and reports. He completed his academic career with a bachelor's degree in business administration, a master's degree in industrial engineering and a doctorate in management and organizational sciences with a focus on digital twins, data quality management and decision-making. |
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