Nome e qualifica del proponente del progetto: 
sb_p_2007685
Anno: 
2020
Abstract: 

Critical Infrastructures (CI) are one of the biggest and the most complex Socio-Technical Systems (STS) deserving particular attention in managing operational risks and safety. In modern industrial plants, for example, an increasing complexity emerges due to tight couplings and interactions among technical and social agents. Besides the technical analysis, it is necessary to consider the influences between human and organizational factors, both in everyday work and in abnormal situations.
The characteristics of incidents involving such complex systems (interdependent, multi-sectoral, multi-stakeholder¿) require analysis of the interactions among functions and agents from different perspectives. These analyses should be able to help identifying transient and potentially hidden interactions and help prioritise actions to cover resilience gaps.
While the traditional approaches (Safety I) try to eliminate causes and improve barriers, which sometimes comes at the cost of increasing the complexity of the system and increasing the risk of error or deviation, the Resilience Engineering (or `Safety II¿) is a complementary approach where attention is focused to the system¿s abilities to perform and to succeed in varying conditions.
Resilience approaches are built on the assumption that not all disruptive events involving complex CI systems can be prevented and that there is a need to create more resilient CIs that can reduce chances of a shock, absorb it and quickly adapt to new contingent or prevailing conditions.
Despite its disruptive and powerful vision, resilience engineering (or `Safety II¿) is still at its infancy, mainly investigated at conceptual and theoretical level, with very limited real world demonstrations and validations.
The research project aims at covering this knowledge gap and answering to the need for safer and more resilient critical infrastructure networks (e.g. railway systems) or installations (e.g. chemical facility).

ERC: 
SH1_10
SH1_9
PE7_3
Componenti gruppo di ricerca: 
sb_cp_is_2533578
Innovatività: 

The starting point for the project will be the latest developments in the field, while leveraging and advancing the previous research carried out at the partnering institutions. The proposed project will adopt capability perspective to analyse and assess the resilience of heterogeneous, interdependent socio-tech systems and support Resilience Improvement Planning (RIP). READ (Resilience Capacities Assessment for Critical Infrastructures Disruptions) framework [14], which has been successfully tested in Lombardy Region, will be further developed and adapted.
The project will extensively use the FRAM as a method to assess the work practices and understand how the variability may resonate, i.e. reinforcing each other dynamically causing emergent phenomena. Highlighting critical functions and critical links between functions the FRAM facilitates the risk analysis, taking account of system¿s responses to different operating conditions and different risk state. The traditional pure FRAM structure work has been enhanced by extending the performance variability concept [15], introducing a semi-quantitative simulation framework [16] and defining a matrix representation of functional resonance usable for network analysis [17]. The project will take advantage of these recently introduced approaches for developing a functional resonance model of a large-scale process in the critical infrastructure domain. The model will be used to define areas of concerns and identify the need for functional performance indicators, capable of addressing the resilience capabilities of the system.
Acknowledging the complexity and symbiotic interactions of current socio-technical systems, a simple structural decomposability is not enough to explain socio-technical mechanisms, as argued by the theory of Resilience Engineering. Therefore, a functional-oriented evolution of the Abstraction Hierarchy, i.e. the Abstraction/Agency framework, will be used to represent large-scale systems and to capture inter-agents functional relationships both intra-level and inter-level. Considering the large-scale critical infrastructure process to be analysed in the project, the FRAM modelling will rely on the Abstraction/Agency as a method to deal with the complexity of the representation and increase the usability of the method.
The RAG framework will be enhanced both in methodological and operational terms. Firstly, the project will analyse the significance of a hierarchical structure used to model the resilience abilities (Analytic Hierarchy Process). The analysis will assess the need for transforming the hierarchy into a network structure in terms of increased complicatedness, modelling benefits, and method usability, exploring similar analytical techniques (Analytic Network Process). Then the definition of the resilience abilities will be contextualized in the critical infrastructure domains both at abstract level (exploring the validity and refine, if necessary, the RAG four cornerstones) and operational level (defining the metrics and actual questions) thus extending the usability of the RAG in a currently under-developed research area. This specific task will take advantages of the insights derived from the application of a multi-layer functional model, as for the Abstraction/Agency-based FRAM.

[14] European READ Project (Resilience Capacities Assessment for Critical Infrastructures Disruption: https://www.read-project.eu/
[15] Bellini, E., Ceravolo, P., & Nesi, P. (2017). Quantify resilience enhancement of UTS through exploiting connected community and Internet of everything emerging technologies. ACM Transactions on Internet Technology (TOIT), 18(1), 7.
[16] Patriarca, R., Di Gravio, G., Costantino, F., 2017. A Monte Carlo evolution of the Functional Resonance Analysis Method (FRAM) to assess performance variability in complex systems. Saf. Sci. 91. doi:10.1016/j.ssci.2016.07.016
[17] Patriarca, R., Del Pinto, G., Di Gravio,G., Costantino, F. (2018). FRAM for Systemic Accident Analysis: A Matrix Representation of Functional Resonance. International Journal of Reliability, Quality and Safety Engineering, 25 (1).

Codice Bando: 
2007685

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