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False Alarms Management by Data Science

  • Ana María Peco ChacónEmail author
  • Fausto Pedro García Márquez
Chapter

Abstract

Due to the development of control system technology over the last years, the number of sensors has increased dramatically and the configuration of alarms in control systems has become easier. It leads to a large number of alarms and increased operator workload. Industrial plants are currently underperforming due to alarm flood, which can cause minor, or even catastrophic, incidents. The businesses are demanding data science to avoid this, it is necessary to use process and alarm data. The industrial plants must understand the entire process and they count on the experience of the operator. It has been considered that collaborative research between academic world and industry should be undertaken to prevent flooding of alarms, both in normal and transitory conditions. New guidelines, standards and scientific/academic research should be developed. Nowadays new statistical, analytical and mathematical tools are being implemented for alarm detection, and the role of the operator must also be taken into account for correct alarm flood resolution. It will lead to a future with safer and more cost-effective industrial systems.

Notes

Acknowledgements

The work reported herewith has been financially supported by the Spanish Ministerio de Economía y Competitividad, under the Research Grants RTC-2016-5694-3 and DPI2015-67264-P.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ana María Peco Chacón
    • 1
    Email author
  • Fausto Pedro García Márquez
    • 1
  1. 1.Ingenium Reseach GroupUniversity of Castilla-La ManchaCiudad RealSpain

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