Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 77-82 |
| Seitenumfang | 6 |
| Fachzeitschrift | Procedia Manufacturing |
| Jahrgang | 40 |
| Publikationsstatus | Veröffentlicht - 4 März 2019 |
| Veranstaltung | 19th Machining Innovations Conference for Aerospace Industry 2019 (MIC 2019) - Hannover, Deutschland Dauer: 27 Nov. 2019 → 28 Nov. 2019 Konferenznummer: 19 |
Abstract
The maintenance, repair and overhaul (MRO) processes of aircraft engines are dominated by a high proportion of manual work and subjective condition assessment of used parts. This leads to inefficiency due to additional, partially not required workload and high scrap rates. Further, there is a lack of knowledge about the effects of the respective repair measures on the performance of the parts. So far, there are no autonomous repair solutions that allow an optimal and individually tailored regeneration. In order to realize such a process, it is necessary to bring together the manufacturing, function-simulating and logistics-oriented disciplines in an integrated system. For this, data management along the process chain is an important success factor. In particular, the provision and linking of the data and data formats required for simulation and the production environment is of fundamental importance. This paper presents a data architecture that can serve as a framework for data integration within a representative process chain for regeneration.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Artificial intelligence
- Ingenieurwesen (insg.)
- Wirtschaftsingenieurwesen und Fertigungstechnik
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in: Procedia Manufacturing, Jahrgang 40, 04.03.2019, S. 77-82.
Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review
}
TY - JOUR
T1 - Towards an autonomous maintenance, repair and overhaul process
T2 - 19th Machining Innovations Conference for Aerospace Industry 2019 (MIC 2019)
AU - Denkena, Berend
AU - Nyhuis, Peter
AU - Bergmann, Benjamin
AU - Nübel, Nicolas
AU - Lucht, Torben
N1 - Conference code: 19
PY - 2019/3/4
Y1 - 2019/3/4
N2 - The maintenance, repair and overhaul (MRO) processes of aircraft engines are dominated by a high proportion of manual work and subjective condition assessment of used parts. This leads to inefficiency due to additional, partially not required workload and high scrap rates. Further, there is a lack of knowledge about the effects of the respective repair measures on the performance of the parts. So far, there are no autonomous repair solutions that allow an optimal and individually tailored regeneration. In order to realize such a process, it is necessary to bring together the manufacturing, function-simulating and logistics-oriented disciplines in an integrated system. For this, data management along the process chain is an important success factor. In particular, the provision and linking of the data and data formats required for simulation and the production environment is of fundamental importance. This paper presents a data architecture that can serve as a framework for data integration within a representative process chain for regeneration.
AB - The maintenance, repair and overhaul (MRO) processes of aircraft engines are dominated by a high proportion of manual work and subjective condition assessment of used parts. This leads to inefficiency due to additional, partially not required workload and high scrap rates. Further, there is a lack of knowledge about the effects of the respective repair measures on the performance of the parts. So far, there are no autonomous repair solutions that allow an optimal and individually tailored regeneration. In order to realize such a process, it is necessary to bring together the manufacturing, function-simulating and logistics-oriented disciplines in an integrated system. For this, data management along the process chain is an important success factor. In particular, the provision and linking of the data and data formats required for simulation and the production environment is of fundamental importance. This paper presents a data architecture that can serve as a framework for data integration within a representative process chain for regeneration.
KW - High-pressure turbine blade
KW - MRO
KW - Virtual workpiece twin
UR - http://www.scopus.com/inward/record.url?scp=85084385256&partnerID=8YFLogxK
U2 - 10.1016/j.promfg.2020.02.014
DO - 10.1016/j.promfg.2020.02.014
M3 - Conference article
VL - 40
SP - 77
EP - 82
JO - Procedia Manufacturing
JF - Procedia Manufacturing
SN - 2351-9789
Y2 - 27 November 2019 through 28 November 2019
ER -