ICALEPCS2015 - List of Authors (Roshchin, M.)

Paper	Title	Page
WEPGF068	Formalizing Expert Knowledge in Order to Analyse CERN's Control Systems	857
	A. Voitier, M. Gonzalez-Berges, F.M. Tilaro CERN, Geneva, Switzerland M. Roshchin Siemens AG, Corporate Technology, München, Germany
	The automation infrastructure needed to reliably run CERN's accelerator complex and its experiments produces large and diverse amounts of data, besides physics data. Over 600 industrial control systems with about 45 million parameters store more than 100 terabytes of data per year. At the same time a large technical expertise in this domain is collected and formalized. The study is based on a set of use cases classified into three data analytics domains applicable to CERN's control systems: online monitoring, fault diagnosis and engineering support. A known root cause analysis concerning gas system alarms flooding was reproduced with Siemens' Smart Data technologies and its results were compared with a previous analysis. The new solution has been put in place as a tool supporting operators during breakdowns in a live production system. The effectiveness of this deployment suggests that these technologies can be applied to more cases. The intended goals would be to increase CERN's systems reliability and reduce analysis efforts from weeks to hours. It also ensures a more consistent approach for these analyses by harvesting a central expert knowledge base available at all times.
	Poster WEPGF068 [1.500 MB]
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Paper

Title

Page

Formalizing Expert Knowledge in Order to Analyse CERN's Control Systems

857

A. Voitier, M. Gonzalez-Berges, F.M. Tilaro
CERN, Geneva, Switzerland
M. Roshchin
Siemens AG, Corporate Technology, München, Germany

The automation infrastructure needed to reliably run CERN's accelerator complex and its experiments produces large and diverse amounts of data, besides physics data. Over 600 industrial control systems with about 45 million parameters store more than 100 terabytes of data per year. At the same time a large technical expertise in this domain is collected and formalized. The study is based on a set of use cases classified into three data analytics domains applicable to CERN's control systems: online monitoring, fault diagnosis and engineering support. A known root cause analysis concerning gas system alarms flooding was reproduced with Siemens' Smart Data technologies and its results were compared with a previous analysis. The new solution has been put in place as a tool supporting operators during breakdowns in a live production system. The effectiveness of this deployment suggests that these technologies can be applied to more cases. The intended goals would be to increase CERN's systems reliability and reduce analysis efforts from weeks to hours. It also ensures a more consistent approach for these analyses by harvesting a central expert knowledge base available at all times.

Poster WEPGF068 [1.500 MB]

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)