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Risk assessment in sociotechnical systems based on functional resonance analysis method and hierarchical fuzzy
Ashish Kumar1, Sudhir Kumar Singh2, Biswajit Samanta2
1Department of Mining Engineering, Indian Institute of Technology, Kharagpur, 721302, India. aksaini4@kgpian.iitkgp.ac.in.
Scientific Reports
|July 3, 2025
Summary
This study introduces an advanced risk assessment methodology for complex socio-technical systems, integrating novel soft computing and natural language processing techniques to enhance safety and prevent accidents.
Area of Science:
- Engineering
- Computer Science
- Risk Management
Background:
- Traditional risk assessment methods struggle with complex socio-technical systems.
- Limitations include capturing systemic complexities and human operator roles.
Purpose of the Study:
- Develop a comprehensive risk assessment methodology for complex socio-technical systems.
- Integrate functional resonance analysis, soft computing, NLP, and multi-criteria decision-making.
Main Methods:
- Utilized Z-numbers for timing and precision variability.
- Employed Z-TOPSIS and hierarchical fuzzy inference systems.
- Applied text classification for amplification factor calculation using near-miss data.
- Analyzed critical couplings, paths, and degree centrality.
Main Results:
- Developed a novel, integrated risk assessment framework.
- Demonstrated effectiveness in an aluminum smelter anode change operation.
- Identified critical functions and influence pathways.
Conclusions:
- The proposed methodology offers a structured, data-driven tool for risk assessment in complex systems.
- Implementation can improve safety, reduce accidents, and prevent economic losses.
- Enhances understanding of systemic interactions and variability propagation.
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