Fadhil Adita Ramadhan , Agus Mansur , Nashrullah Setiawan , Mohd Rizal Salleh
{"title":"基于模糊推理和风险屋的钢铁制造供应链风险缓解分析框架","authors":"Fadhil Adita Ramadhan , Agus Mansur , Nashrullah Setiawan , Mohd Rizal Salleh","doi":"10.1016/j.sca.2025.100122","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":101186,"journal":{"name":"Supply Chain Analytics","volume":"10 ","pages":"Article 100122"},"PeriodicalIF":0.0000,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An analytical risk mitigation framework for steel fabrication supply chains using fuzzy inference and house of risk\",\"authors\":\"Fadhil Adita Ramadhan , Agus Mansur , Nashrullah Setiawan , Mohd Rizal Salleh\",\"doi\":\"10.1016/j.sca.2025.100122\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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.</div></div>\",\"PeriodicalId\":101186,\"journal\":{\"name\":\"Supply Chain Analytics\",\"volume\":\"10 \",\"pages\":\"Article 100122\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Supply Chain Analytics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2949863525000226\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Supply Chain Analytics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949863525000226","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An analytical risk mitigation framework for steel fabrication supply chains using fuzzy inference and house of risk
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.