DOAJ Open Access 2025

An analytical risk mitigation framework for steel fabrication supply chains using fuzzy inference and house of risk

Fadhil Adita Ramadhan Agus Mansur Nashrullah Setiawan Mohd Rizal Salleh

Abstrak

This study integrates the House of Risk (HOR) approach with the Fuzzy Inference System (FIS) to manage supply chain risks in steel fabrication by addressing market uncertainties and operational challenges to enhance stability and productivity. The study begins with risk identification using HOR and the calculation of fuzzy aggregate risk priority (FARP) based on severity and frequency. A Mamdani based FIS is then applied to prioritize risks and develop mitigation strategies, leveraging data from expert interviews and literature reviews. The findings highlight supplier order failures as the top risk with the highest FARP score, leading to the proposal of 50 mitigation actions, including managed inventory systems and supplier diversification, to strengthen supply chain resilience and reduce vulnerabilities. However, this study is limited to the steel fabrication industry and relies on expert opinions and secondary data, which may affect generalizability. Future research can apply this approach to other industries and incorporate realtime data for validation. The proposed mitigation strategies offer actionable insights for supply chain managers, helping companies improve operational stability and adapt effectively to market uncertainties. By introducing an integrated HOR and FIS approach, this study provides a dynamic and systematic framework for comprehensive supply chain risk management, offering original insights to the field.

Penulis (4)

F

Fadhil Adita Ramadhan

A

Agus Mansur

N

Nashrullah Setiawan

M

Mohd Rizal Salleh

Format Sitasi

Ramadhan, F.A., Mansur, A., Setiawan, N., Salleh, M.R. (2025). An analytical risk mitigation framework for steel fabrication supply chains using fuzzy inference and house of risk. https://doi.org/10.1016/j.sca.2025.100122

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Informasi Jurnal
Tahun Terbit
2025
Sumber Database
DOAJ
DOI
10.1016/j.sca.2025.100122
Akses
Open Access ✓