A human error risk priority number calculation methodology using fuzzy and TOPSIS grey

Abstract

In the implementation of management error proofing, enterprises need to carry out risk evaluation and ranking of management activities error, to determine error proofing improvement order. We note that management function failure is different from industrial failure, and the management activity error as its cause is also different from operational or device error, so the method generally used in industry is not suitable for the risk assessment of management activity error. To address this issue, this study integrates the FMEA (failure modes and effect analysis) with the ISO9001 standardized management system framework describing multilevel and multi-attribute management activities, and the human errors that may lead to functional failure of quality management activities are identified at each level and each category. The three factors (severity (S), occurrence (O), and detection (D)) of errors in each management activity are evaluated and integrated into the risk priority number for each quality management activity error. The two major defects of the traditional FMEA in the practical application process are as follows: (1) the evaluation of error attributes of various management activities is basically qualitative language description, which cannot be quantified; (2) the other one disadvantage is that it ignores the fact that three factors have the different weights in the system rather than equality, and not considering the relative importance of between them. In this article, the fuzzy set theory and the grey relational decision theory are, respectively, applied to improve the two defects and to improve the accuracy of the decision. Finally, a numerical example of a coal mine is given to verify the effectiveness of the proposed method. This study provides a basis for managers and practitioners to quantitatively evaluate and prevent errors in management activities.