Details
| Original language | English |
|---|---|
| Pages (from-to) | 107-112 |
| Number of pages | 6 |
| Journal | Procedia Manufacturing |
| Volume | 52 |
| Publication status | Published - 24 Dec 2020 |
| Event | 5th International Conference on System-Integrated Intelligence - Bremen, Germany Duration: 11 Nov 2020 → 13 Nov 2020 Conference number: 5 |
Abstract
The global trend towards the comprehensive digitisation of technologies in product manufacturing is leading to radical changes in engineering processes and requires a new extended understanding of data handling. The amounts of data to be considered are becoming larger and more complex. Data can originate from process simulations, machines used or subsequent analyses, which together with the resulting components serve as a complete and reproducible description of the process. Within the Collaborative Research Centre”Process Chain for Manufacturing of Hybrid High Performance Components by Tailored Forming”, interdisciplinary work is being carried out on the development of process chains for the production of hybrid components. The management of the generated data and descriptive metadata, the support of the process steps and preliminary and subsequent data analysis are fundamental challenges. The objective is a continuous, standardised data management according to the FAIR Data Principles so that process-specific data and parameters can be transferred together with the components or samples to subsequent processes, individual process designs can take place and processes of machine learning can be accelerated. A central element is the collaborative development of a domain-specific ontology for a semantic description of data and processes of the entire process chain.
Keywords
- Digitisation of Scientific Data, FAIR Data Principles, Manufacturing Process Chains, Ontology Development, Research Data Management
ASJC Scopus subject areas
- Engineering(all)
- Industrial and Manufacturing Engineering
- Computer Science(all)
- Artificial Intelligence
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In: Procedia Manufacturing, Vol. 52, 24.12.2020, p. 107-112.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Development of a domain-specific ontology to support research data management for the tailored forming technology
AU - Sheveleva, Tatyana
AU - Koepler, Oliver
AU - Mozgova, Iryna
AU - Lachmayer, Roland
AU - Auer, Sören
N1 - Conference code: 5
PY - 2020/12/24
Y1 - 2020/12/24
N2 - The global trend towards the comprehensive digitisation of technologies in product manufacturing is leading to radical changes in engineering processes and requires a new extended understanding of data handling. The amounts of data to be considered are becoming larger and more complex. Data can originate from process simulations, machines used or subsequent analyses, which together with the resulting components serve as a complete and reproducible description of the process. Within the Collaborative Research Centre”Process Chain for Manufacturing of Hybrid High Performance Components by Tailored Forming”, interdisciplinary work is being carried out on the development of process chains for the production of hybrid components. The management of the generated data and descriptive metadata, the support of the process steps and preliminary and subsequent data analysis are fundamental challenges. The objective is a continuous, standardised data management according to the FAIR Data Principles so that process-specific data and parameters can be transferred together with the components or samples to subsequent processes, individual process designs can take place and processes of machine learning can be accelerated. A central element is the collaborative development of a domain-specific ontology for a semantic description of data and processes of the entire process chain.
AB - The global trend towards the comprehensive digitisation of technologies in product manufacturing is leading to radical changes in engineering processes and requires a new extended understanding of data handling. The amounts of data to be considered are becoming larger and more complex. Data can originate from process simulations, machines used or subsequent analyses, which together with the resulting components serve as a complete and reproducible description of the process. Within the Collaborative Research Centre”Process Chain for Manufacturing of Hybrid High Performance Components by Tailored Forming”, interdisciplinary work is being carried out on the development of process chains for the production of hybrid components. The management of the generated data and descriptive metadata, the support of the process steps and preliminary and subsequent data analysis are fundamental challenges. The objective is a continuous, standardised data management according to the FAIR Data Principles so that process-specific data and parameters can be transferred together with the components or samples to subsequent processes, individual process designs can take place and processes of machine learning can be accelerated. A central element is the collaborative development of a domain-specific ontology for a semantic description of data and processes of the entire process chain.
KW - Digitisation of Scientific Data
KW - FAIR Data Principles
KW - Manufacturing Process Chains
KW - Ontology Development
KW - Research Data Management
UR - http://www.scopus.com/inward/record.url?scp=85100824785&partnerID=8YFLogxK
U2 - 10.1016/j.promfg.2020.11.020
DO - 10.1016/j.promfg.2020.11.020
M3 - Conference article
AN - SCOPUS:85100824785
VL - 52
SP - 107
EP - 112
JO - Procedia Manufacturing
JF - Procedia Manufacturing
SN - 2351-9789
T2 - 5th International Conference on System-Integrated Intelligence
Y2 - 11 November 2020 through 13 November 2020
ER -