An Intelligent Fuzzy Functional Resonance Analysis Model on System Safety and Human Factors

Esmaeil Zarei; Mohammad Yazdi; Brian J. Roggow; Ahmad BahooToroody

doi:10.1007/978-3-031-39774-5_88

An Intelligent Fuzzy Functional Resonance Analysis Model on System Safety and Human Factors

Esmaeil Zarei^*, Mohammad Yazdi, Brian J. Roggow, Ahmad BahooToroody

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

2 Citations (Scopus)

Abstract

System safety and human factors analysis are pivotal in critical operations from healthcare to aviation and aerospace. Conventional safety and human factors models cannot model emergent risks that can seriously threaten organizational life. To this end, this research has developed a novel Interval-Valued Spherical Fuzzy Sets (IVSFS)-Functional Resonance Analysis (IVSFS-FRA) model to analyze system safety and human factors in critical socio-technical systems. The proposed model deals with critical concerns in knowledge acquisition and captures emerging risks in critical operations. An actual industrial maintenance cycle has been investigated to demonstrate the model's capabilities and effectiveness. The model can recognize evolving and emerging critical resonances, address uncertainty, and reveal tight couplings in complex systems. Accordingly, the proposed model can prevent system disruption and enhance system resilience by allocating timely and cost-effective safety countermeasures.

Original language	English
Title of host publication	Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
Editors	Cengiz Kahraman, Irem Ucal Sari, Basar Oztaysi, Sezi Cevik Onar, Selcuk Cebi, A. Çağrı Tolga
Publisher	Springer
Pages	808-815
Number of pages	8
ISBN (Print)	978-3-031-39773-8
DOIs	https://doi.org/10.1007/978-3-031-39774-5_88
Publication status	Published - 2023
MoE publication type	A4 Conference publication
Event	International Conference on Intelligent and Fuzzy Systems - Istanbul, Türkiye Duration: 22 Aug 2023 → 24 Aug 2023 Conference number: 5

Publication series

Name	Lecture Notes in Networks and Systems
Volume	758 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	International Conference on Intelligent and Fuzzy Systems
Abbreviated title	INFUS
Country/Territory	Türkiye
City	Istanbul
Period	22/08/2023 → 24/08/2023

Keywords

Intelligence systems
Risk Analysis
Soft Computing

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-031-39774-5_88

Cite this

Zarei, E., Yazdi, M., Roggow, B. J., & BahooToroody, A. (2023). An Intelligent Fuzzy Functional Resonance Analysis Model on System Safety and Human Factors. In C. Kahraman, I. U. Sari, B. Oztaysi, S. Cevik Onar, S. Cebi, & A. Ç. Tolga (Eds.), Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference (pp. 808-815). (Lecture Notes in Networks and Systems; Vol. 758 LNNS). Springer. https://doi.org/10.1007/978-3-031-39774-5_88

Zarei, Esmaeil ; Yazdi, Mohammad ; Roggow, Brian J. et al. / An Intelligent Fuzzy Functional Resonance Analysis Model on System Safety and Human Factors. Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference. editor / Cengiz Kahraman ; Irem Ucal Sari ; Basar Oztaysi ; Sezi Cevik Onar ; Selcuk Cebi ; A. Çağrı Tolga. Springer, 2023. pp. 808-815 (Lecture Notes in Networks and Systems).

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abstract = "System safety and human factors analysis are pivotal in critical operations from healthcare to aviation and aerospace. Conventional safety and human factors models cannot model emergent risks that can seriously threaten organizational life. To this end, this research has developed a novel Interval-Valued Spherical Fuzzy Sets (IVSFS)-Functional Resonance Analysis (IVSFS-FRA) model to analyze system safety and human factors in critical socio-technical systems. The proposed model deals with critical concerns in knowledge acquisition and captures emerging risks in critical operations. An actual industrial maintenance cycle has been investigated to demonstrate the model's capabilities and effectiveness. The model can recognize evolving and emerging critical resonances, address uncertainty, and reveal tight couplings in complex systems. Accordingly, the proposed model can prevent system disruption and enhance system resilience by allocating timely and cost-effective safety countermeasures.",

keywords = "Intelligence systems, Risk Analysis, Soft Computing",

author = "Esmaeil Zarei and Mohammad Yazdi and Roggow, {Brian J.} and Ahmad BahooToroody",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference on Intelligent and Fuzzy Systems, INFUS ; Conference date: 22-08-2023 Through 24-08-2023",

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Zarei, E, Yazdi, M, Roggow, BJ & BahooToroody, A 2023, An Intelligent Fuzzy Functional Resonance Analysis Model on System Safety and Human Factors. in C Kahraman, IU Sari, B Oztaysi, S Cevik Onar, S Cebi & AÇ Tolga (eds), Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference. Lecture Notes in Networks and Systems, vol. 758 LNNS, Springer, pp. 808-815, International Conference on Intelligent and Fuzzy Systems, Istanbul, Türkiye, 22/08/2023. https://doi.org/10.1007/978-3-031-39774-5_88

An Intelligent Fuzzy Functional Resonance Analysis Model on System Safety and Human Factors. / Zarei, Esmaeil; Yazdi, Mohammad; Roggow, Brian J. et al.
Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference. ed. / Cengiz Kahraman; Irem Ucal Sari; Basar Oztaysi; Sezi Cevik Onar; Selcuk Cebi; A. Çağrı Tolga. Springer, 2023. p. 808-815 (Lecture Notes in Networks and Systems; Vol. 758 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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T1 - An Intelligent Fuzzy Functional Resonance Analysis Model on System Safety and Human Factors

AU - Zarei, Esmaeil

AU - Yazdi, Mohammad

AU - Roggow, Brian J.

AU - BahooToroody, Ahmad

N1 - Conference code: 5

PY - 2023

Y1 - 2023

N2 - System safety and human factors analysis are pivotal in critical operations from healthcare to aviation and aerospace. Conventional safety and human factors models cannot model emergent risks that can seriously threaten organizational life. To this end, this research has developed a novel Interval-Valued Spherical Fuzzy Sets (IVSFS)-Functional Resonance Analysis (IVSFS-FRA) model to analyze system safety and human factors in critical socio-technical systems. The proposed model deals with critical concerns in knowledge acquisition and captures emerging risks in critical operations. An actual industrial maintenance cycle has been investigated to demonstrate the model's capabilities and effectiveness. The model can recognize evolving and emerging critical resonances, address uncertainty, and reveal tight couplings in complex systems. Accordingly, the proposed model can prevent system disruption and enhance system resilience by allocating timely and cost-effective safety countermeasures.

AB - System safety and human factors analysis are pivotal in critical operations from healthcare to aviation and aerospace. Conventional safety and human factors models cannot model emergent risks that can seriously threaten organizational life. To this end, this research has developed a novel Interval-Valued Spherical Fuzzy Sets (IVSFS)-Functional Resonance Analysis (IVSFS-FRA) model to analyze system safety and human factors in critical socio-technical systems. The proposed model deals with critical concerns in knowledge acquisition and captures emerging risks in critical operations. An actual industrial maintenance cycle has been investigated to demonstrate the model's capabilities and effectiveness. The model can recognize evolving and emerging critical resonances, address uncertainty, and reveal tight couplings in complex systems. Accordingly, the proposed model can prevent system disruption and enhance system resilience by allocating timely and cost-effective safety countermeasures.

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KW - Soft Computing

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DO - 10.1007/978-3-031-39774-5_88

M3 - Conference article in proceedings

AN - SCOPUS:85172013081

SN - 978-3-031-39773-8

T3 - Lecture Notes in Networks and Systems

SP - 808

EP - 815

BT - Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference

A2 - Kahraman, Cengiz

A2 - Sari, Irem Ucal

A2 - Oztaysi, Basar

A2 - Cevik Onar, Sezi

A2 - Cebi, Selcuk

A2 - Tolga, A. Çağrı

PB - Springer

T2 - International Conference on Intelligent and Fuzzy Systems

Y2 - 22 August 2023 through 24 August 2023

ER -

Zarei E, Yazdi M, Roggow BJ, BahooToroody A. An Intelligent Fuzzy Functional Resonance Analysis Model on System Safety and Human Factors. In Kahraman C, Sari IU, Oztaysi B, Cevik Onar S, Cebi S, Tolga AÇ, editors, Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference. Springer. 2023. p. 808-815. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-39774-5_88