Real-Time Risk Assessment and Decision Support

  • Type:
    Conference Presentation
  • Conference Type:
    AIChE Spring Meeting and Global Congress on Process Safety
  • Presentation Date:
    April 1, 2014
  • Duration:
    30 minutes
  • Skill Level:
    Intermediate
  • PDHs:
    0.50

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Managers and operators of major hazard facilities make complex decisions in hazardous situations as a part of their daily work activity. These decisions are made against the background potential for a major accident.

Such decisions may be required to account for a large number of factors including plant condition and performance, operational status, knowledge and experience of personnel, interactions with other activities, and the effectiveness of processes. The information involved in the decision comes from multiple sources and may be difficult to assess.

Technical risk assessments provide a useful picture of major accident risk but some widely accepted approaches suffer from some significant problems which limit their value as tools for operational decision making. Problems may include:

  • The time requirement for a technical risk assessment
  • The omission of competence, experience and other human factors from the assessment
  • Use of generic industry-average failure data that may not reflect actual equipment condition
  • Limited or no account of incident/ accident history
  • Inspection, test and maintenance findings not recognised
  • Inability to account for day-to-day changes in operational status
  • No credit for audits, safety critical system performance etc.

The paper describes DNV’s investigations into an approach that addresses many of these difficulties; it illustrates how risks can be monitored in real-time and so enables safer decision making. The method is applicable to the assessment of a wide range of major accident hazard scenarios. The paper will describe how the tool addresses problems in the traditional approach to QRA. Notably, the method performs a risk assessment, but also identifies the probable causes of potential failure scenarios. The speed of the assessment points to its potential in real-time detection and control systems

The method employs a Bayesian net to perform the risk assessment. Bayesian nets have been used to aid decision making in many different situations and industries, but have received relatively little attention as risk assessment and decision tools in major hazard industries. The paper will include a description of the benefits offered by this technology as well as a view of its limitations. The speaker will give a real-time demonstration of the method.

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