Soft computing for nonlinear risk assessment of complex socio-technical systems
•A novel soft computing application for risk assessment in socio-technical systems is proposed.•Outputs of the FRAM method were computed using a fuzzy inference system.•The framework was applied to a recycling of construction waste process.•The risk priority for the key activities of the model is de...
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| Published in: | Expert systems with applications Vol. 206; p. 117828 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
15.11.2022
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| ISSN: | 0957-4174, 1873-6793 |
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| Abstract | •A novel soft computing application for risk assessment in socio-technical systems is proposed.•Outputs of the FRAM method were computed using a fuzzy inference system.•The framework was applied to a recycling of construction waste process.•The risk priority for the key activities of the model is determined.
Work in socio-technical systems (STS) exhibits dynamic and complex behaviors, becoming difficult to model, evaluate and predict. This study develops an integrated soft computing approach for nonlinear risk assessment in STS: the functional resonance analysis method (FRAM) has been integrated with fuzzy sets. While FRAM is helpful to model performance variability in qualitative terms, the assessments are usually subjected to a high degree of uncertainty. This novel approach is meant to overcome the subjectivity associated with the qualitative analyses performed by experts’ judgments required by FRAM. For demonstration purposes, the approach has been applied to model a waste recycling process for construction materials. The results show how the approach allows assessing and ranking critical activities in STS operations. |
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| AbstractList | •A novel soft computing application for risk assessment in socio-technical systems is proposed.•Outputs of the FRAM method were computed using a fuzzy inference system.•The framework was applied to a recycling of construction waste process.•The risk priority for the key activities of the model is determined.
Work in socio-technical systems (STS) exhibits dynamic and complex behaviors, becoming difficult to model, evaluate and predict. This study develops an integrated soft computing approach for nonlinear risk assessment in STS: the functional resonance analysis method (FRAM) has been integrated with fuzzy sets. While FRAM is helpful to model performance variability in qualitative terms, the assessments are usually subjected to a high degree of uncertainty. This novel approach is meant to overcome the subjectivity associated with the qualitative analyses performed by experts’ judgments required by FRAM. For demonstration purposes, the approach has been applied to model a waste recycling process for construction materials. The results show how the approach allows assessing and ranking critical activities in STS operations. |
| ArticleNumber | 117828 |
| Author | Carolina Rosa, Ana de Souza, Ivenio Teixeira Patriarca, Riccardo Haddad, Assed |
| Author_xml | – sequence: 1 givenname: Ivenio Teixeira surname: de Souza fullname: de Souza, Ivenio Teixeira email: ivenio@poli.ufrj.br organization: Programa de Engenharia Ambiental, Universidade Federal do Rio de Janeiro, Brazil – sequence: 2 givenname: Ana surname: Carolina Rosa fullname: Carolina Rosa, Ana email: carolinarosa@poli.ufrj.br organization: Programa de Engenharia Ambiental, Universidade Federal do Rio de Janeiro, Brazil – sequence: 3 givenname: Riccardo surname: Patriarca fullname: Patriarca, Riccardo email: riccardo.patriarca@uniroma1.it organization: Sapienza University of Rome, Department of Mechanical and Aerospace Engineering, Italy – sequence: 4 givenname: Assed surname: Haddad fullname: Haddad, Assed email: assed@poli.ufrj.br organization: Programa de Engenharia Ambiental, Universidade Federal do Rio de Janeiro, Brazil |
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