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PT Notes

Engineering Judgment and Expert Opinion in Hazard and Risk Analysis

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The risk of process plant accidents is managed with hazard and risk analysis methods such as the hazard and operability (HAZOP) study, risk matrices, layers of protection analysis (LOPA), and quantitative risk analysis (QRA). Hazard and risk analysis studies depend heavily on subjective human decision making in the form of engineering judgment and expert opinion. A variety of human and psychological factors impact the behavior and decisions of people. Considerable reliance is placed on the use of engineering judgment and expert opinion in hazard and risk analysis studies which employ a significant amount of subjective judgment. Human judgments may be flawed because they are influenced by cognitive biases which may invalidate study results. Hazard scenarios may be missed, risks may be estimated incorrectly, and important recommendations for risk reduction may be omitted. Consequently, effort should be made to minimize the influence of cognitive biases on decisions made during studies.

Engineering judgment and expert opinion enter into hazard and risk analysis in various ways. Examples of tasks that use engineering judgment in hazard analysis are:

  • Evaluating process safety information
  • Defining design intent for a process and deviations to consider
  • Identifying credible hazard scenarios
  • Assessing the credibility of scenarios
  • Qualifying process controls as safeguards
  • Estimating the likelihoods and consequences of scenarios
  • Answering checklist questions
  • Formulating recommendations for risk reduction
  • Deciding how much team discussion to allow

Examples of tasks that use expert opinion in hazard analysis are:

  • Choosing a hazard analysis method
  • Subdividing a process for study
  • Identifying possible actions by operators, mechanics, and other process personnel

Examples of tasks that use engineering judgment in risk analysis are:

  • Structuring a risk model
  • Selecting incident outcomes and incident outcome cases
  • Modeling common cause and other dependent failures
  • Selecting risk measures and criteria

Examples of tasks that use expert opinion in risk analysis are:

  • Enhancing sparse input data
  • Assessing uncertainties in data

These tasks require many decisions to be made. All the decisions are subject to the adverse effects of cognitive biases. Hazard analysis often is performed by groups of people and risk analysis usually involves a number of analysts. Thus, not only are cognitive biases that affect individuals important but also those that address individuals working together and groups of people must be considered.

Suggestions for mitigating cognitive biases in hazard and risk analysis studies include:

  • Be knowledgeable of the underlying causes of different cognitive biases. This knowledge can help in mitigating them.
  • Ensure practitioners are aware of and understand the full range of possible cognitive biases so that they are in a better position to recognize them in fellow practitioners.
  • Train practitioners within particular domains so that knowledge overcomes cognitive bias. For example, training to improve understanding of process design intent.
  • Use as much tangible data and information as possible to avoid the need to rely on engineering judgment and expert opinion.
  • Provide practitioners with personalized feedback regarding ways in which they exhibit bias.
  • Encourage practitioners to adopt an attitude of healthy skepticism towards views expressed by others.
  • Encourage practitioners to look not just for evidence to confirm expressed views but also evidence to the contrary.
  • Encourage practitioners to take the perspective of a person who will experience the consequences of their decisions.
  • Employ a devil’s advocate whose role is to challenge and debate views offered by others in order to help determine their validity.
  • Avoid cognitive overload during studies. Cognitive biases may be more prevalent under these circumstances.

Hazard and risk analysis studies require the expenditure of considerable resources. Their results should not be invalidated by the lack of consideration of cognitive biases during studies.

Further information on these issues is provided in:

The validity of engineering judgment and expert opinion in hazard and risk analysis: The influence of cognitive biases. Process Safety Progress, Volume 37, pages 205 - 210, Issue 2, June 2018.

Process safety incidents, cognitive biases and critical thinking, Hydrocarbon Processing, Volume 96, Number 4, pages 81 - 82, April 2017.

Cognitive biases in process hazard analysis, J. of Loss Prevention in the Process Industries, Volume 43, pages 372 - 377, 2016.

The role of people and human factors in performing process hazard analysis and layers of protection analysis, J. of Loss Prevention in the Process Industries, Volume 26, pages 1352 - 1365, 2013.

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