UMMUMM
Jurnal Teknik IndustriJurnal Teknik IndustriSupply chains play a critical role in the operational success of organizations, impacting both costs and product quality. However, they are often exposed to various risks that can disrupt business processes. This research aims to identify supply chain risks and propose mitigation strategies using the House of Risk (HOR) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) methods. Through interviews, key issues were identified in a fiberglass companys supply chain, including raw material supply fluctuations, procurement cost variability, defective materials, inappropriate specifications, outdated technology, insufficient worker skills, and ambitious company targets. The novelty of this study lies in the application of MOORA, which introduces a correlation matrix for risk mitigation by considering both cost minimization and benefit maximization. The analysis identified 12 risk agents and 26 risk events, which were prioritized using HOR stage 2 with the MOORA method. The top preventive actions were ranked, providing actionable recommendations for companies to address supply chain risks more effectively. The findings of this research offer practical insights for companies in the fiberglass industry to enhance supply chain resilience by integrating cost and benefit considerations into their risk management strategies.
This research successfully identified and mapped risks within the supply chain using the SCOR model, pinpointing 12 risk agents and 26 risk events.The House of Risk (HOR) methodology, combined with the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method, facilitated the prioritization of mitigation strategies.The studys findings provide actionable recommendations for companies, particularly in the fiberglass industry, to enhance supply chain resilience by integrating cost-benefit considerations into their risk management approaches.
Future research should explore the integration of additional decision-making tools to complement the House of Risk and MOORA methods, potentially enhancing the robustness of risk mitigation strategies. Furthermore, investigating the impact of external factors, such as market dynamics and regulatory changes, on the effectiveness of these strategies would provide a more comprehensive understanding of supply chain risk management. Finally, a promising avenue for future study involves developing a dynamic risk assessment model that continuously monitors and adapts to evolving supply chain conditions, allowing for proactive identification and mitigation of emerging threats. This could involve utilizing real-time data analytics and machine learning techniques to predict potential disruptions and optimize mitigation efforts, ultimately strengthening supply chain resilience and ensuring operational continuity.
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