An integrated approach to a predictive and ranking model of use error using fuzzy BWM and fuzzy TOPSIS.

Abstract

Avoiding error in handling artifacts is crucial for achieving a high level of system reliability and safety assessment. This study develops a predictive and ranking model of use error (PRUE). In the first phase, use errors are systematically detected and anticipated via an inquiry process in two levels (activity and function). In the second phase, the fuzzy best-worst method (F-BWM) is employed to determine relative weights of three criteria including consequence of use error (CUE), detection of use error (DUE) and probability of use error (PUE). Fuzzy TOPSIS is then employed to rank use errors according to their risk level. The use errors of an infant ventilator device are assessed to demonstrate applicability of the PRUE method. The results of the present study confirm the reliability and applicability of this approach to assess artifact use errors. Moreover, the PRUE method can be utilized in investigation of user interface design.