The step complexity measure for emergency operating procedures: measure verification

Abstract

In complex systems, such as nuclear power plants (NPPs) or airplane control systems, human errors play a major role in many accidents. Therefore, to prevent an occurrence of accidents or to ensure system safety, extensive effort has been made to identify significant factors that can cause human errors. According to related studies, written manuals or operating procedures are revealed as one of the most important factors, and the understandability is pointed out as one of the major reasons for procedure-related human errors. Many qualitative checklists are suggested to evaluate emergency operating procedures (EOPs) of NPPs. However, since qualitative evaluations using checklists have some drawbacks, a quantitative measure that can quantify the complexity of EOPs is very necessary to compensate for them. In order to quantify the complexity of steps included in EOPs, Park et al. suggested the step complexity (SC) measure. In addition, to ascertain the appropriateness of the SC measure, averaged step performance time data obtained from emergency training records for the loss of coolant accident and the excess steam dump event were compared with estimated SC scores. Although averaged step performance time data show good correlation with estimated SC scores, conclusions for some important issues that have to be clarified to ensure the appropriateness of the SC measure were not properly drawn because of lack of backup data. In this paper, to clarify remaining issues, additional activities to verify the appropriateness of the SC measure are performed using averaged step performance time data obtained from emergency training records. The total number of available records is 36, and training scenarios are the steam generator tube rupture and the loss of all feedwater . The number of scenarios is 18 each. From these emergency training records, averaged step performance time data for 30 steps are retrieved. As the results, the SC measure shows statistically meaningful correlation with averaged step performance time data. In addition, since it is observed that the SC measure seems to have the procedure independent property (i.e. steps that have similar SC scores, whether they are included in different procedures or not, would have similar step performance time), it can be concluded that the SC measure can represent the complexity of steps included in EOPs.