Details
| Original language | English |
|---|---|
| Title of host publication | Springer Series in Advanced Manufacturing |
| Publisher | Springer Nature |
| Pages | 1-11 |
| Number of pages | 11 |
| ISBN (electronic) | 978-3-030-77539-1 |
| ISBN (print) | 978-3-030-77538-4 |
| Publication status | Published - 2022 |
Publication series
| Name | Springer Series in Advanced Manufacturing |
|---|---|
| ISSN (Print) | 1860-5168 |
| ISSN (electronic) | 2196-1735 |
Abstract
As a recently coined buzzword without a clear definition, Digital Twin relies on the high-fidelity digital representation of the physical product and the continuously accumulated data and real-time presentation of the collected data to simultaneously update and modify with its physical counterpart. In research and practice, many types and expressions of Digital Twin take place for plethora of use cases along the product lifecycle. The simulation of production processes using a Digital Twin can be utilised for prospective planning, analysis of existing systems or process-parallel monitoring. In all cases, the Digital Twin provides manufacturing companies various benefits for improvement in production and logistics processes leading to cost savings and higher flexibility. The generation of the Digital Twin in a built environment poses a huge challenge—in particular for small and medium-sized enterprises. For this market segment, appropriate concepts and solutions need to be elaborated and developed, including modern IT techniques such as Machine Learning. In this introductory chapter, the approach used to pave the way for this book is presented. The idea of Digital Twin, the origins, the goals and the expected audience of this book are roughly described. Finally, we give the first insight in the content of this book and the mutual interdependence of the chapters. This book explores the way to generate and commercialize the Digital Twin in manufacturing in order to provide a convincing offering as the outcome of a public-founded research project.
Keywords
- Configuration lifecycle management, Digital twin, Manufacturing, Product lifecycle management, Production process
ASJC Scopus subject areas
- Engineering(all)
- Industrial and Manufacturing Engineering
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Springer Series in Advanced Manufacturing. Springer Nature, 2022. p. 1-11 (Springer Series in Advanced Manufacturing).
Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review
}
TY - CHAP
T1 - Introduction to the Book
AU - Stjepandić, Josip
AU - Sommer, Markus
AU - Stobrawa, Sebastian
AU - Denkena, Berend
N1 - Funding Information: This book explores the results of the research project “DigiTwin—Efficient Generation of a Digital Twin in the Manufacturing” conducted by four partners supported by the German Federal Ministry of Education and Research (BMBF) within the framework concept “KMU innovativ” in period 2018–2020. In the communication with the funding agency, this project was evaluated as the particularly successful and worth for further dissemination [20]. Therefore, it was decided to present its outcome to a broader audience. The editors were representatives of their research organizations. The authors were members of the project team.
PY - 2022
Y1 - 2022
N2 - As a recently coined buzzword without a clear definition, Digital Twin relies on the high-fidelity digital representation of the physical product and the continuously accumulated data and real-time presentation of the collected data to simultaneously update and modify with its physical counterpart. In research and practice, many types and expressions of Digital Twin take place for plethora of use cases along the product lifecycle. The simulation of production processes using a Digital Twin can be utilised for prospective planning, analysis of existing systems or process-parallel monitoring. In all cases, the Digital Twin provides manufacturing companies various benefits for improvement in production and logistics processes leading to cost savings and higher flexibility. The generation of the Digital Twin in a built environment poses a huge challenge—in particular for small and medium-sized enterprises. For this market segment, appropriate concepts and solutions need to be elaborated and developed, including modern IT techniques such as Machine Learning. In this introductory chapter, the approach used to pave the way for this book is presented. The idea of Digital Twin, the origins, the goals and the expected audience of this book are roughly described. Finally, we give the first insight in the content of this book and the mutual interdependence of the chapters. This book explores the way to generate and commercialize the Digital Twin in manufacturing in order to provide a convincing offering as the outcome of a public-founded research project.
AB - As a recently coined buzzword without a clear definition, Digital Twin relies on the high-fidelity digital representation of the physical product and the continuously accumulated data and real-time presentation of the collected data to simultaneously update and modify with its physical counterpart. In research and practice, many types and expressions of Digital Twin take place for plethora of use cases along the product lifecycle. The simulation of production processes using a Digital Twin can be utilised for prospective planning, analysis of existing systems or process-parallel monitoring. In all cases, the Digital Twin provides manufacturing companies various benefits for improvement in production and logistics processes leading to cost savings and higher flexibility. The generation of the Digital Twin in a built environment poses a huge challenge—in particular for small and medium-sized enterprises. For this market segment, appropriate concepts and solutions need to be elaborated and developed, including modern IT techniques such as Machine Learning. In this introductory chapter, the approach used to pave the way for this book is presented. The idea of Digital Twin, the origins, the goals and the expected audience of this book are roughly described. Finally, we give the first insight in the content of this book and the mutual interdependence of the chapters. This book explores the way to generate and commercialize the Digital Twin in manufacturing in order to provide a convincing offering as the outcome of a public-founded research project.
KW - Configuration lifecycle management
KW - Digital twin
KW - Manufacturing
KW - Product lifecycle management
KW - Production process
UR - http://www.scopus.com/inward/record.url?scp=85151532005&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-77539-1_1
DO - 10.1007/978-3-030-77539-1_1
M3 - Contribution to book/anthology
AN - SCOPUS:85151532005
SN - 978-3-030-77538-4
T3 - Springer Series in Advanced Manufacturing
SP - 1
EP - 11
BT - Springer Series in Advanced Manufacturing
PB - Springer Nature
ER -