Paper Info
Title
Data-Driven Valve Diagnosis To Increase The Overall Equipment Effectiveness In Process Industry
Abstract
The avoidance of plant shutdowns is one of the highest priorities for plant operators (plant owners). Shutdowns are forced by abnormal situations, e.g. unexpected equipment faults such as valve or pump faults. Each unexpected fault can lead to hazardous situations within a plant. Pumps are already well analyzed compared to valves and also frequently used in process industry. In this paper a data-driven fault detection system for valves will be introduced. To gain additional knowledge about faults of specific equipment, big data technology is applied, based on a huge number of historical data for different valves. The paper introduces an approach in which data from different competitive companies operating several process plants are filtered, selected and combined with data from equipment manufacturers. The valve diagnosis system uses historical process data obtained across company borders using physical valve models to detect faults by comparing standardized flow coefficient determined by DIN IEC 60534-2-1.
Year
Venue
Field
2016
2016 IEEE 14TH INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN)
Data modeling,Overall equipment effectiveness,Data-driven,Work in process,Fault detection and isolation,Flow coefficient,Real-time computing,Engineering,Hazardous waste,Electrical engineering,Big data,Reliability engineering
DocType
ISSN
Citations 
Conference
1935-4576
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Jens Folmer1448.37
Carolin Schrufer200.34
Julian Fuchs300.34
Christian Vermum400.34
Vogel-Heuser, B.5521125.47