Unveil key functions in socio-technical systems: mapping FRAM into a multilayer network

Abstract

Network theory has been widely used to describe many complex systems belonging to several fields from physics to sociology. Particularly interesting are multilayer networks which concurrently account for several types of relationships, without necessarily aggregating them. The functional resonance analysis method (FRAM) is an agnostic method (i.e., not making modeling assumptions) allowing semantically rich descriptions of the relationships among functions constituting a socio-technical system. This richness may soon become overwhelming in case of not trivial FRAM models. A multilayer network represents a promising choice for combining the long-proven experience in network theory with the FRAM’s agnosticism. On these observations, this article shows how a FRAM model can be reinterpreted as a five-layer multilayer-directed network without any loss of information, even reducing the cognitive workload required for the analysts. This paper defines a methodology able to prioritize potentially critical functions through dedicated network centrality descriptors, and to generate instantiations for comparison and benchmarking of scenario-based envisioned solutions. A walk-through application in industrial operations management confirms the feasibility and validity of the proposed methodology.

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Notes

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    An input is considered as any input, i.e., Input, Precondition, Resource, Control, Time.

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Acknowledgments

The authors of this paper developed an IT solution based on VBA (Patriarca et al. 2018a) to perform the calculation over the FRAM instantiation and utilized the muxViz tool to measure multilayer centrality indexes (De Domenico et al. 2015).

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Correspondence to Andrea Falegnami.

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Falegnami, A., Costantino, F., Di Gravio, G. et al. Unveil key functions in socio-technical systems: mapping FRAM into a multilayer network. Cogn Tech Work 22, 877–899 (2020). https://doi.org/10.1007/s10111-019-00612-0

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Keywords

  • Organizational dissonance
  • Decision making
  • Complex networks
  • Industrial operations
  • Resilience engineering
  • Safety-II