Details
| Titel in Übersetzung | Adaptive maintenance - Condition-based maintenance by means of distributed data management and artificial intelligence |
|---|---|
| Originalsprache | Deutsch |
| Seiten (von - bis) | 333-338 |
| Seitenumfang | 6 |
| Fachzeitschrift | Zeitschrift für wirtschaftlichen Fabrikbetrieb (ZWF) (online) |
| Jahrgang | 105 |
| Ausgabenummer | 4 |
| Publikationsstatus | Veröffentlicht - Apr. 2010 |
Abstract
Condition-based maintenance of production equipment offers a better trade-off between availability and maintenance costs than other maintenance strategies. A novel approach for determining and predicting the plant condition is presented. The approach applies methods of artificial intelligence to a distributed database covering the entire life cycle of the equipment. The approach simplifies the introduction of condition-based maintenance by means of machine learning and is especially suited for equipment with unknown fault behaviour.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Allgemeiner Maschinenbau
- Betriebswirtschaft, Management und Rechnungswesen (insg.)
- Strategie und Management
- Entscheidungswissenschaften (insg.)
- Managementlehre und Operations Resarch
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in: Zeitschrift für wirtschaftlichen Fabrikbetrieb (ZWF) (online), Jahrgang 105, Nr. 4, 04.2010, S. 333-338.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Lernfähige Instandhaltung
T2 - Zustandsorientierte Instandhaltung durch verteilte Datenhaltung und Künstliche Intelligenz
AU - Heißmeyer, Sven
AU - Altmann, Dirk
AU - Overmeyer, Ludger
PY - 2010/4
Y1 - 2010/4
N2 - Condition-based maintenance of production equipment offers a better trade-off between availability and maintenance costs than other maintenance strategies. A novel approach for determining and predicting the plant condition is presented. The approach applies methods of artificial intelligence to a distributed database covering the entire life cycle of the equipment. The approach simplifies the introduction of condition-based maintenance by means of machine learning and is especially suited for equipment with unknown fault behaviour.
AB - Condition-based maintenance of production equipment offers a better trade-off between availability and maintenance costs than other maintenance strategies. A novel approach for determining and predicting the plant condition is presented. The approach applies methods of artificial intelligence to a distributed database covering the entire life cycle of the equipment. The approach simplifies the introduction of condition-based maintenance by means of machine learning and is especially suited for equipment with unknown fault behaviour.
UR - http://www.scopus.com/inward/record.url?scp=77952982727&partnerID=8YFLogxK
U2 - 10.3139/104.110294
DO - 10.3139/104.110294
M3 - Artikel
AN - SCOPUS:77952982727
VL - 105
SP - 333
EP - 338
JO - Zeitschrift für wirtschaftlichen Fabrikbetrieb (ZWF) (online)
JF - Zeitschrift für wirtschaftlichen Fabrikbetrieb (ZWF) (online)
SN - 0947-0085
IS - 4
ER -