Risk significance assessment on the basis of a fuzzy model

Abstract

The paper considers the problem of risk significance assessment in the activity of a testing laboratory. The accreditation criteria of such laboratories include requirements for implementation of risk management in the organization of their activity. To optimize the risk management process, it is proposed to create an expert system based on fuzzy modelling of the derivation of the risk significance assessment. The expediency of this approach is justified by the expert nature of information on the parameters of risks, subjectivity and uncertainty in their assessments. A description of the subject area “Risk significance assessment” is given, groups of input features and an output parameter are established, the corresponding linguistic variables are introduced, basic and extended term-sets are defined, membership functions are constructed. A fuzzy expert knowledge base has been created, the fuzzy inference of assessing the significance of risks is based on. The proposed algorithm for assessing the significance of risk was tested, confirming its suitability and effectiveness for creating an expert system.