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@InProceedings{nissen:icalepcs2019-wempr004,
author = {H. Nissen and S. Grau},
title = {{Why Should You Invest in Asset Management? A Fire and Gas Use Case}},
booktitle = {Proc. ICALEPCS'19},
pages = {1041--1045},
paper = {WEMPR004},
language = {english},
keywords = {detector, database, software, SCADA, MMI},
venue = {New York, NY, USA},
series = {International Conference on Accelerator and Large Experimental Physics Control Systems},
number = {17},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {08},
year = {2020},
issn = {2226-0358},
isbn = {978-3-95450-209-7},
doi = {10.18429/JACoW-ICALEPCS2019-WEMPR004},
url = {https://jacow.org/icalepcs2019/papers/wempr004.pdf},
note = {https://doi.org/10.18429/JACoW-ICALEPCS2019-WEMPR004},
abstract = {At present, the CERN Fire and Gas detection systems involve about 22500 sensors and their number is increasing rapidly at the same time as the number of equipped installations grows up. These assets cover a wide spectrum of technologies, manufacturers, models, parameters, and ages, reflecting the 60 years of CERN history. The use of strict rules and data structures in the declaration of the assets can make a big impact on the overall system maintainability and therefore on the global reliability of the installation. Organized assets data facilitates the creation of powerful reports that help asset owners and management address material obsolescence and end-of-life concerns with a global perspective Historically preventive maintenance have been used to assure the correct function of the installations. With modern supervision systems, a lot of data is collected and can be used to move from preventive maintenance towards data driven maintenance (predictive). Moreover it optimizes maintenance cost and increase system availability while maintaining reliability. A prerequisite of this move is a coherence on the assets defined in the asset management system and in the supervision system.},
}