A Fuzzy Cognitive Maps Tool for Developing a RBI&M Model

A proper maintenance plan is directly related to the definition of critical indexes for ensuring a high level of safety and high level in service quality for all equipments in the plants. The traditional approach, according to risk‐based inspection and maintenance (RBI&M), requires that each parameter considered in the definition of critical indexes shall be divided into intervals in order to assign it a score. By the elaboration of these scores, the critical indexes are calculated. However, what are the rules that allow the company the definition of the range and the assignment of the relative score? Are these rules subjective or objectives? Literature in the field highlights that these decisions are often carried out by maintenance managers. In order to overcome this approach, in this paper, a method based on Fuzzy Cognitive Maps (FCMs) is presented. FCMs have been used for structuring and supporting decisional processes. The criticality of equipments is described in terms of concepts affecting its functioning. No ranges or scores are defined, but only structural and functional features are considered in order to define a criticality index. The resulting fuzzy model can be used to analyse, simulate, test the influence of concepts and predict the behaviour of the system. The RBI&M model, proposed in this work, has been analysed through a case study of an Italian refinery.