Global Semiconductor Supply Chain Risk Assessment and Mitigation: A Novel TSF-AHP-FMEA Framework

This study assesses global semiconductor supply chain risks from the perspective of developing economies, a segment that faces heightened geopolitical and technological vulnerabilities. We propose a novel hybrid framework that combines the T-spherical fuzzy set (TSF)-based Analytical Hierarchy Process (TSF-AHP) and a modified TSF-Failure Mode and Effects Analysis (TSF-FMEA). The framework leverages TSF to address uncertainty and subjectivity in expert evaluations, using TSF-AHP to derive risk weights and a modified TSF-FMEA (with experience-weighted opinions) to compute a unique Risk Priority Index. Key prioritized risks identified include trade policy changes, geopolitical disruptions, demand fluctuations, and raw material volatility. This model provides a robust assessment tool to prioritize risk to enhance supply chain resilience in complex and uncertain global business environments.

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Publication Details

Journal
International Journal of Computational Intelligence Systems
Published
2026-02-27
DOI
https://doi.org/10.1007/s44196-026-01223-0
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Global Semiconductor Supply Chain Risk Assessment and Mitigation: A Novel TSF-AHP-FMEA Framework

M. P. Akhtar, Muhammad Mustafa Kamal, Radim Lenort, Hamidreza Namazi et al.
International Journal of Computational Intelligence Systems
Supply Chain Resilience and Risk Management
article

Global Semiconductor Supply Chain Risk Assessment and Mitigation: A Novel TSF-AHP-FMEA Framework

M. P. Akhtar, Muhammad Mustafa Kamal, Radim Lenort, Hamidreza Namazi, Md Gulzarull Hasan
article en

Abstract

This study assesses global semiconductor supply chain risks from the perspective of developing economies, a segment that faces heightened geopolitical and technological vulnerabilities. We propose a novel hybrid framework that combines the T-spherical fuzzy set (TSF)-based Analytical Hierarchy Process (TSF-AHP) and a modified TSF-Failure Mode and Effects Analysis (TSF-FMEA). The framework leverages TSF to address uncertainty and subjectivity in expert evaluations, using TSF-AHP to derive risk weights and a modified TSF-FMEA (with experience-weighted opinions) to compute a unique Risk Priority Index. Key prioritized risks identified include trade policy changes, geopolitical disruptions, demand fluctuations, and raw material volatility. This model provides a robust assessment tool to prioritize risk to enhance supply chain resilience in complex and uncertain global business environments.

International Journal of Computational Intelligence SystemsVol. 19(1)
University of Jordan (JO), Monash University Malaysia (MY), Galgotias University (IN), Manipal Academy of Higher Education (IN), Kyoto University (JP), University of Exeter (GB), Škoda (Czechia) (CZ), Škoda Auto University (CZ)
Openalex Percentile: Top 44%
Supply Chain Resilience and Risk Management
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