Evolution of the Functional Resonance Analysis Method (FRAM) through the combination with other methods

  1. Pardo-Ferreira, M. C.
  2. Martínez-Rojas, M. 1
  3. Salguero-Caparrós, F. 1
  4. Rubio-Romero, J. C. 1
  1. 1 Escuela de Ingenierías Industriales Dpto. de Economía y Administración de Empresas Universidad de Málaga Calle Doctor Ortiz Ramos s/n. 29071, Málaga
Revista:
Dirección y organización: Revista de dirección, organización y administración de empresas

ISSN: 1132-175X

Año de publicación: 2019

Número: 68

Páginas: 41-50

Tipo: Artículo

DOI: 10.37610/DYO.V0I68.550 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Dirección y organización: Revista de dirección, organización y administración de empresas

Resumen

Traditionally, simple and complex linear models were used to analyze accidents and find their causes. The Resilience Engineering breaks with the traditional way of understanding safety focused on things that go wrong. In this way, the concept of safety is redefined to focus on things that go well. The new paradigm of Resilience Engineering emphasizes that when things go well in difficult circumstances, it is mainly due to the ability of workers to adapt, that is, their ability to recognize and absorb unexpected changes and events. In this new context, Functional Resonance Analysis Method enables to model how a system works and to understand the variability in daily performance. The objective of this research study is to present the main approaches that combine other methods with FRAM with the aim of improving it, as for example: Monte Carlo simulation, Fuzzy Logic theory, Model Checking, Analytical Hierarchical Process methodologies and Abstraction Hierarchy. Notice that the present study develops a non-exhaustive review of the methods that appears most frequently in the scientific Literature. The search process has been carried out in the main scientific databases such as Web of Knowledge, Science Direct or Google Scholar since they are identified as relevant to the research domain. In order to obtain adequate results concerning the objective of this work, we consider “Functional Resonance Analysis Method” as terms to perform the search in the title, abstract and keyword fields. After the data collection process, a total of 22 documents were obtained. Subsequently, all the retrieved documents were filtered by selecting those publications that had the purpose of combining the FRAM with another method to define the function variability in a semi-quantitative or quantitative manner. Then, after this filtering process, 18 studies were analysed and presented from diverse perspectives. Firstly, an analysis was conducted to explore the evolution of this research domain over time. As a result of this analysis, a growing trend in the publication of research is observed, both journal documents and conference documents. Secondly, an analysis concerning the sector where the study is focused is detailed since all the analyzed studies included an application example of their proposal. In this sense, the aviation sector was the one that appeared most frequently, followed by the maritime sector. Thirdly, the distribution of analysed studies on the basis of the country of authors has been presented, being Italy and China the reference countries in this research domain. Following, an analysis in relation to the journals where the documents are published is conducted. Finally, the proposals were grouped according to the different approaches that were combined with FRAM. As a general conclusion, the analysis of the new FRAM approaches shows that all the authors coincide in preserving the theoretical basis of FRAM for modeling complex systems. Despite this, there is still no approach that prevails over others and future research should continue to advance the evolution the Functional Resonance Analysis Method with the aim to facilitate the risk assessments in complex systems.Keywords: Functional Resonance Analysis Method; Resilience Engineering, Complex systems; Risk assessment; Safety.

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Información de financiación

We wish to thank the Spanish Ministry of Economy and Competitiveness for financing project BIA2016-79270-P, of which this paper forms a part, and the postdoctoral contract (FJCI-2015-24093). It is also important to acknowledge the Ministry of Education, Culture and Sports of the Government of Spain for it support through the predoctoral contracts (FPU 2016/03298)

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