Quantitative assessment of resilience engineering in process industries through a novel multi-attribute group decision-making algorithm using interval type-2 fuzzy sets

Abstract

Nowadays, the promotion of technology has increased the complexity of socio-technical systems, which has led to severe disasters. Human errors and defects in components of a system have previously been recognized as the most important causes of accidents. Still, recent studies have emphasized that the causes of accidents, especially in complex socio-technical systems (CSS), depend on organizational factors, functional changes, and combining a set of unexpected events. With the transition from the traditional static approach to systems, and due to the two features of high interconnectivity and the complexity of modern systems, a new approach called resilience engineering (RE) has been introduced. On the other hand, sophisticated socio-technical systems have a high level of uncertainty that its modeling requires considering tools for dealing with this kind of intricate uncertainty, such as interval type-2 fuzzy sets (IT2FS). In this paper, focusing on process industries, a new algorithm based on multi-criteria group decision-making for evaluating departments of a process industry from RE using the concept of type-2 fuzzy sets is presented. To do this, by introducing the RE criteria in process industries, their weights are calculated as incomplete information received from the decision-makers (DMs). The incompleteness of information is due to the uncertainties in the evaluation of criteria. Then different alternatives are ranked using IT2FS. It is shown that the presented algorithm is relatively consistent with other approaches, and besides simplicity, it has good stability for dealing with different weights for the criteria.