Scope: an intelligent maintenance system for supporting crew operations

Author(s):  
Leo Breebaart Andre Bos
2017 ◽  
Vol 107 (07-08) ◽  
pp. 530-535
Author(s):  
T. Miebach ◽  
M. Schmidt ◽  
P. Prof. Nyhuis

Der Fachbeitrag stellt eine Methode vor, mit der sich Bibliotheken von Instandhaltungsmaßnahmen selbstlernend gestalten lassen. Die „Intelligenz“ solcher Systeme bietet mehrfachen Nutzen, einerseits durch die Auswahl der passenden Instandhaltungsmethode zum richtigen Zeitpunkt, andererseits durch die damit verbundene Erhöhung des kompletten Abnutzungsvorrates. Die Ergebnisse sind im Sonderforschungsbereich 653 „Gentelligente Bauteile im Lebenszyklus – Nutzung vererbbarer, bauteilinhärenter Informationen in der Produktionstechnik“ entstanden.   This article describes a method to design a self-learning maintenance library. The benefit derived from the intelligence of those systems refers to the right choice of maintenance measures at the right time and the enhancement of the whole wear margin. The results are part of the Collaborative Research Centre 653: Gentelligent components in their lifecycle – Utilization of inheritable component information in product engineering.


2014 ◽  
Vol 536-537 ◽  
pp. 454-460
Author(s):  
Zhi Xin Yang ◽  
Chen Lei

With the emerging of RFID technology and increasing pressure on maintenance, higher request is posed on the maintenance action. This paper introduces a combined intelligent system to complete the maintenance task. SVM and SVR model has been trained to classify machine fault types and predict the degradation. The proposed system can carry out maintenance action with the staff position information form RFID tags and the machine condition information. Genetic algorithm will be used to search the best maintenance sequence, then, the combined information will help make most efficient maintenance decision.


2014 ◽  
Vol 47 (3) ◽  
pp. 7116-7121 ◽  
Author(s):  
Marcos Zuccolotto ◽  
Luca Fasanotti ◽  
Sergio Cavalieri ◽  
Carlos Eduardo Pereira

2004 ◽  
Vol 55 (1) ◽  
pp. 61-67 ◽  
Author(s):  
Enrique A. Sierra ◽  
Juan J. Quiroga ◽  
Roberto Fernández ◽  
Gustavo E. Monte

2008 ◽  
Vol 375-376 ◽  
pp. 530-534
Author(s):  
Sheng Li Song ◽  
Chong Yu Xiao ◽  
Qi Cai Zhou ◽  
Wan Li Li ◽  
Yu Qing Tang ◽  
...  

The remote monitoring and intelligent maintenance is one of the most important criteria for evaluating a product or a service. This paper focuses on the large asphalt mixing plant, an internet/intranet technology-based Browser/Server structure model of remote intelligent maintenance system for asphalt mixing plant is designed. The critical technologies of realizing the system which include the fieldbus-based data collection technology, the database technology, the intelligent fault diagnosis technology as well as the ASP technology are deeply studied respectively. The remote monitoring and intelligent maintenance system will well provide an effective and efficient activity that meets the customers’ requirements and satisfaction.


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