Author: Tilaro, F.M.
Paper Title Page
WEPGF068 Formalizing Expert Knowledge in order to Analyse CERN's Control Systems 1
 
  • 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.  
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