Latest revision as of 09:53, 16 February 2021

Abstract

Due to the continuous increment in complexity of the socio-technical systems, decision makers call for new methods which are able to support timely as well as accurate decision-making related to resilience management. The current methods tend to be polarized on: efficiency-thoroughness forcing decision makers in making decisions on the base of resource availability instead of the problem to be solved. This paper presents a new fast-forward, cost-effective, and thorough enough framework to quantify resilience of a complex socio-technical system. The approach extends the functional resonance analysis method (FRAM) with a numerical method for the quantification of the analysis (Q-FRAM). In particular, it has been extended and operationalized the qualitative concepts of functional variability and dumping capacities into a method in which key performance indicators are derived from the model and aggregated into four indicators representing the FRAM resilience cornerstones (anticipate, respond, monitor, learn) through a bottom-up hierarchical approach. Finally, the four indicators are composed in a unique system resilience index that expresses the total variability present in the system at instant t . A numerical example of the use of the framework is provided together with a validation based on a comparison of the proposed approach with the current landscape.

Original document

The different versions of the original document can be found in:

• http://hdl.handle.net/11591/418271

• https://ieeexplore.ieee.org/ielx7/4267003/9020228/08686178.pdf

• http://xplorestaging.ieee.org/ielx7/4267003/9020228/08686178.pdf?arnumber=8686178,

http://dx.doi.org/10.1109/jsyst.2019.2905713

• https://dblp.uni-trier.de/db/journals/sj/sj14.html#BelliniCN20,

https://ieeexplore.ieee.org/document/8686178,

https://flore.unifi.it/handle/2158/1179694,

https://academic.microsoft.com/#/detail/2943244548