Application of a process mining technique to identifying information navigation characteristics of human operators working in a digital main control room – feasibility study

Abstract

It is well known that one of the major contributors to the significant events of socio-technical systems is a human error. Accordingly, various kinds of human reliability analysis techniques have been proposed for many decades, which allow us to properly estimate human error probabilities. However, one of the urgent challenges is to quantify human error probabilities when required tasks are conducted in a control room equipped with up-to-date digital equipment (e.g., digital main control room) because existing techniques are mainly focusing on an analog control room. In this regard, it is necessary to carefully understand how professional operators in the digital control room carry out the required tasks. Therefore, in this study, information navigation characteristics (i.e., information gathering behaviors observable from professional operators who need to conduct the required tasks by using given digital equipment) were analyzed based on process mining techniques. To this end, event logs were collected from the professional operators of domestic nuclear power plants who were exposed to simulated off-normal conditions in a digital main control room. As a result, it seems that process mining techniques are useful for extracting crucial information needed for the human reliability analysis in the digital main control room.