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

  • Andrea FalegnamiEmail author
  • Francesco Costantino
  • Giulio Di Gravio
  • Riccardo Patriarca
Original Article
  • 52 Downloads

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.

Keywords

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

Notes

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).

References

  1. Bellamy LJ, Chambon M, Van Guldener V (2018) Getting resilience into safety programs using simple tools—a research background and practical implementation. Reliab Eng Syst Saf 172:171–184.  https://doi.org/10.1016/j.ress.2017.12.005 CrossRefGoogle Scholar
  2. Bellini E, Nesi P, Pantaleo G, Venturi A (2016) Functional resonance analysis method based-decision support tool for urban transport system resilience management. In: IEEE 2nd International Smart Cities Conference: Improving the Citizens Quality of Life, ISC2 2016, Proceedings. IEEE, pp 1–7Google Scholar
  3. Bellini E, Ceravolo P, Nesi P (2017) Quantify resilience enhancement of UTS through exploiting connected community and internet of everything emerging technologies. ACM Trans Internet Technol 18:1–34.  https://doi.org/10.1145/3137572 CrossRefGoogle Scholar
  4. Borgatti SP (2005) Centrality and network flow. Soc Networks 27:55–71.  https://doi.org/10.1016/J.SOCNET.2004.11.008 CrossRefGoogle Scholar
  5. Bródka P, Kazienko P (2014) Multilayered social networks. Encyclopedia of Social network analysis and mining. Springer, New York, pp 998–1013Google Scholar
  6. Colville I, Brown AD, Pye A (2012) Simplexity: sensemaking, organizing and storytelling for our time. Hum Relat 65:5–15.  https://doi.org/10.1177/0018726711425617 CrossRefGoogle Scholar
  7. De Domenico M (2017) Multilayer modeling and analysis of human brain networks. Gigascience 6:1–8.  https://doi.org/10.1093/gigascience/gix004 CrossRefGoogle Scholar
  8. De Domenico M, Solé-Ribalta A, Cozzo E et al (2014) Mathematical formulation of multilayer networks. Phys Rev X.  https://doi.org/10.1103/PhysRevX.3.041022 CrossRefGoogle Scholar
  9. De Domenico M, Porter MA, Arenas A (2015) MuxViz: a tool for multilayer analysis and visualization of networks. J Complex Networks 3:159–176.  https://doi.org/10.1093/comnet/cnu038 CrossRefGoogle Scholar
  10. Duan G, Tian J, Wu J (2015) Extended FRAM by integrating with model checking to effectively explore hazard evolution. Math Probl Eng 2015:1–11.  https://doi.org/10.1155/2015/196107 CrossRefGoogle Scholar
  11. Eppinger SD, Browning TR (2012) Design structure matrix methods and applications. MIT Press, CambridgeCrossRefGoogle Scholar
  12. Ferreira PNP, Cañas JJ (2019) Assessing operational impacts of automation using functional resonance analysis method. Cogn Technol Work.  https://doi.org/10.1007/s10111-019-00540-z CrossRefGoogle Scholar
  13. Franssen M, Kroes P, Reydon TAC, Vermaas PE (2014) Introduction: the ontology of technical artefacts. Artefact kinds. Springer International Publishing, Cham, pp 1–14CrossRefGoogle Scholar
  14. Gattola V, Patriarca R, Tomasi G, Tronci M (2018) Functional resonance in industrial operations: a case study in a manufacturing plant. IFAC-PapersOnLine 51:927–932.  https://doi.org/10.1016/j.ifacol.2018.08.489 CrossRefGoogle Scholar
  15. Gros C (2015) Complex and adaptive dynamical systems. Springer International Publishing, ChamCrossRefGoogle Scholar
  16. Hedberg B (1981) How organizations learn and unlearn. In: Nystrom PC, Starbuck WH (eds) Handbook of organizational design. 1: adapting organizations to their environments. Oxford University Press, OxfordGoogle Scholar
  17. Hofstadter DR (1999) Gödel, Escher, Bach : an eternal golden braid. Basic BooksGoogle Scholar
  18. Hollnagel E (2009) The ETTO principle: Efficiency-thoroughness trade-off: why things that go right sometimes go wrong. Ashgate Publishing LtdGoogle Scholar
  19. Hollnagel E (2012a) Fram: the functional resonance analysis methodGoogle Scholar
  20. Hollnagel E (2012b) FRAM: the functional resonance analysis method: modelling complex socio-technical systems. Ashgate Publishing, FarnhamGoogle Scholar
  21. Hollnagel E (2016) A FRAM Glossary. http://functionalresonance.com/a-fram-glossary.html. Accessed 20 Mar 2019
  22. Horvat E, Zweig KA (2014) Multiplex networks. In: Alhajj R, Rokne J (eds) Encyclopedia of social network analysis and mining. Springer, New York, pp 1019–1023Google Scholar
  23. Johannesson P, Perjons E (2014) Knowledge types and forms. An introduction to design science. Springer International Publishing, Cham, pp 21–38Google Scholar
  24. Kivelä M, Arenas A, Barthelemy M et al (2014) Multilayer networks. J Complex Networks.  https://doi.org/10.1093/comnet/cnu016 CrossRefGoogle Scholar
  25. Lam A (2000) Tacit knowledge, organizational learning and societal institutions: an integrated framework. Organ Stud 21:487–513.  https://doi.org/10.1177/0170840600213001 CrossRefGoogle Scholar
  26. Lee J, Chung H (2018) A new methodology for accident analysis with human and system interaction based on FRAM: case studies in maritime domain. Saf Sci 109:57–66.  https://doi.org/10.1016/J.SSCI.2018.05.011 CrossRefGoogle Scholar
  27. Lü L, Chen D, Ren X-L et al (2016) Vital nodes identification in complex networks. Phys Rep 650:1–63.  https://doi.org/10.1016/J.PHYSREP.2016.06.007 MathSciNetCrossRefGoogle Scholar
  28. Lundberg J, Woltjer R (2013) The Resilience Analysis Matrix (RAM): Visualizing functional dependencies in complex socio-technical systems. Proc 5th Resil Eng Assoc Symp 103–108Google Scholar
  29. Madhavan R, Grover R (1998) From embedded knowledge to embodied knowledge: new product development as knowledge management. J Mark 62:1.  https://doi.org/10.2307/1252283 CrossRefGoogle Scholar
  30. Masys A (2018) Radicalization and recruitment: A systems approach to understanding violent extremism—new developments through FRAM. In: Systems research for real-world challenges. pp 322–348Google Scholar
  31. Newman MEJ (2018) Networks, 2nd edn. Oxford University Press, OxfordCrossRefGoogle Scholar
  32. Patriarca R, Bergström J (2017) Modelling complexity in everyday operations: functional resonance in maritime mooring at quay. Cogn Technol Work in press:  https://doi.org/10.1007/s10111-017-0426-2 CrossRefGoogle Scholar
  33. Patriarca R, Bergström J, Di Gravio G (2017a) Defining the functional resonance analysis space: combining abstraction hierarchy and FRAM. Reliab Eng Syst Saf 165:34–46.  https://doi.org/10.1016/j.ress.2017.03.032 CrossRefGoogle Scholar
  34. Patriarca R, Del Pinto G, Di Gravio G et al (2017b) FRAM for systemic accident analysis: a matrix representation of functional resonance. Int J Reliab Qual Saf Eng 25:1850001.  https://doi.org/10.1142/S0218539318500018 CrossRefGoogle Scholar
  35. Patriarca R, Di Gravio G, Costantino F (2017c) A monte carlo evolution of the functional resonance analysis method (FRAM) to assess performance variability in complex systems. Saf Sci.  https://doi.org/10.1016/j.ssci.2016.07.016 CrossRefGoogle Scholar
  36. Patriarca R, Di Gravio G, Costantino F, Tronci M (2017d) The functional resonance analysis method for a systemic risk based environmental auditing in a sinter plant: a semi-quantitative approach. Environ Impact Assess Rev 63:72–86.  https://doi.org/10.1016/j.eiar.2016.12.002 CrossRefGoogle Scholar
  37. Patriarca R, Di Gravio G, Costantino F (2018a) MyFRAM: an open tool support for the functional resonance analysis method. In: 2017 2nd International Conference on System Reliability and Safety, ICSRS 2017, pp 439–443Google Scholar
  38. Patriarca R, Falegnami A, Costantino F, Bilotta F (2018b) Resilience engineering for socio-technical risk analysis: application in neuro-surgery. 180:321–335Google Scholar
  39. Patriarca R, Falegnami A, De Nicola A et al (2019) Serious games for industrial safety: an approach for developing resilience early warning indicators. Saf Sci.  https://doi.org/10.1016/j.ssci.2019.05.031 CrossRefGoogle Scholar
  40. Patton MQ (2002) Qualitative research and evaluation methods, 3rd editio. Sage Publications, Thousand OaksGoogle Scholar
  41. Raben DC, Bogh SB, Viskum B et al (2017) Proposing leading indicators for blood sampling: application of a method based on the principles of resilient healthcare. Cogn Technol Work 19:809–817.  https://doi.org/10.1007/s10111-017-0437-z CrossRefGoogle Scholar
  42. Raîche G, Walls TA, Magis D et al (2013) Non-graphical solutions for Cattell’s scree test. Methodology 9:23–29.  https://doi.org/10.1027/1614-2241/a000051 CrossRefGoogle Scholar
  43. Rosa LV, Haddad AN, De Carvalho PVR (2015) Assessing risk in sustainable construction using the functional resonance analysis method (FRAM). Cogn Technol Work 17:559–573.  https://doi.org/10.1007/s10111-015-0337-z CrossRefGoogle Scholar
  44. Rosa LV, França JEM, Haddad AN, Carvalho PVR (2017) A resilience engineering approach for sustainable safety in green construction. J Sustain Dev Energy, Water Environ Syst 5:480–495.  https://doi.org/10.13044/j.sdewes.d5.0174 CrossRefGoogle Scholar
  45. Ruault J-R, Vanderhaegen F, Kolski C (2013) Sociotechnical systems resilience: a dissonance engineering point of view. IFAC Proc 46:149–156.  https://doi.org/10.3182/20130811-5-US-2037.00042 CrossRefGoogle Scholar
  46. Saberian J, Malek MR, Winter S, Hamrah M (2014) A new framework for solving the spatial network problems based on line graphs. Trans GIS 18:767–782.  https://doi.org/10.1111/tgis.12064 CrossRefGoogle Scholar
  47. Simon HA (1996) The sciences of the artificial, vol 3. MIT Press, CambridgeGoogle Scholar
  48. Smith D, Veitch B, Khan F, Taylor R (2017) Understanding industrial safety: comparing Fault tree, Bayesian network, and FRAM approaches. J Loss Prev Process Ind 45:88–101.  https://doi.org/10.1016/J.JLP.2016.11.016 CrossRefGoogle Scholar
  49. Tian J, Wu J, Yang Q, Zhao T (2016) FRAMA: a safety assessment approach based on functional resonance analysis method. Saf Sci 85:41–52.  https://doi.org/10.1016/J.SSCI.2016.01.002 CrossRefGoogle Scholar
  50. Vanderhaegen F, Carsten O (2017) Can dissonance engineering improve risk analysis of human–machine systems? Cogn Technol Work 19:1–12.  https://doi.org/10.1007/s10111-017-0405-7 CrossRefGoogle Scholar
  51. Wachs P, Righi AW, Saurin TA (2019) The functional resonance analysis method as a debriefing tool in scenario-based-training. Springer, Cham, pp 132–138Google Scholar
  52. Wears RL (2017) Rasmussen number greater than one. Appl Ergon 59:592–597.  https://doi.org/10.1016/j.apergo.2016.01.014 CrossRefGoogle Scholar
  53. Woods DD, Hollnagel E, Woods David D (2006) Prologue: resilience engineering concepts. In: Hollnagel E, Woods DD, Leveson NG (eds) Resilience engineering: concepts and precepts. Ashgate Publishing, Farnham, pp 1–6Google Scholar
  54. Yang Q, Tian J, Zhao T (2017) Safety is an emergent property: illustrating functional resonance in Air Traffic Management with formal verification. Saf Sci 93:162–177.  https://doi.org/10.1016/j.ssci.2016.12.006 CrossRefGoogle Scholar
  55. Yu H, Braun P, Yildirim MA et al (2008) High-quality binary protein interaction map of the yeast interactome network. Science 322:104–110.  https://doi.org/10.1126/science.1158684 CrossRefGoogle Scholar
  56. Zheng Z, Tian J, Zhao T (2016) Refining operation guidelines with model-checking-aided FRAM to improve manufacturing processes: a case study for aeroengine blade forging. Cogn Technol Work.  https://doi.org/10.1007/s10111-016-0391-1 CrossRefGoogle Scholar
  57. Zuo Y, Zhao J, Xu K (2016) Word network topic model: a simple but general solution for short and imbalanced texts. Knowl Inf Syst 48:379–398.  https://doi.org/10.1007/s10115-015-0882-z CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Mechanical and Aerospace EngineeringSapienza University of RomeRomeItaly

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