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      A dynamic version of the FRAM for capturing variability in complex operations

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          Abstract

          Functional Resonance Analysis Method (FRAM) is a function-based approach to model complex socio-technical systems and to manage variability. The current FRAM related tools are unable to capture qualitative and quantitative characteristics of variability as well as temporal variations. This study presents in detail a dynamic FRAM-based tool, which is called DynaFRAM. It is introduced to address the variability-related deficiencies of the FRAM related tools. It aims to capture variability in complex operations. It is a dynamic tool developed to capture time related variations in complex operations. This increases the attractiveness of the DynaFRAM for complex operations where specialists and practitioners make decisions in complicated situations. The ability of the DynaFRAM is demonstrated by examining a healthcare related case study. Although the ability of the DynaFRAM is assessed through capturing variations in healthcare operations, it can be applied to other domains in a similar manner.

          • The DynaFRAM is a dynamic FRAM-based tool.

          • It is able to captures different characteristics of variability.

          • It facilitates understanding and analysis of variability in complex operations.

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          Most cited references21

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          Framing the FRAM: A literature review on the functional resonance analysis method

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            A Monte Carlo evolution of the Functional Resonance Analysis Method (FRAM) to assess performance variability in complex systems

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              Application of a non-linear model to understand healthcare processes: using the functional resonance analysis method on a case study of the early detection of sepsis

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                Author and article information

                Contributors
                Journal
                MethodsX
                MethodsX
                MethodsX
                Elsevier
                2215-0161
                02 April 2021
                2021
                02 April 2021
                : 8
                : 101333
                Affiliations
                [a ]Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, Canada
                [b ]Research Services, Horizon Health Network, Saint John Regional Hospital, St. John’s, Canada
                Author notes
                [* ]Corresponding author. vsalehi@ 123456mun.ca
                Article
                S2215-0161(21)00126-6 101333
                10.1016/j.mex.2021.101333
                8374388
                34430239
                b683921a-c090-4454-9919-65f307597681
                © 2021 The Author(s). Published by Elsevier B.V.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 22 January 2021
                : 10 March 2021
                : 26 March 2021
                Categories
                Method Article

                variability,temporal variations,instantiation,healthcare operations

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