A Study on the Multi-level Risk Management System of Power Grid Material Supply Chain Based on Dynamic Data
With the rapid development of the economy, supply chain risk issues have become increasingly prominent, posing a threat to the growth of enterprises. To “identify” the risk factors in the supply chain of power enterprises and reduce the risk of supply chain disruptions, it is urgently necessary to conduct a scientific evaluation of supply chain risks by incorporating dynamically changing risk data. From the perspective of supply chain operations and business processes, this paper constructs a risk monitoring and identification system that adapts to real-time data fluctuations. The foundation of this system is a comprehensive evaluation model based on the Analytic Hierarchy Process (AHP) and the Fuzzy Comprehensive Evaluation method. This model integrates cyclical and stable data from the power grid materials to quantify risks. Using the high-voltage fuse supply chain of a power grid enterprise as an example, the risk level of this product’s supply chain was determined. The proposed supply chain risk management model not only enables real-time monitoring of daily operations but also provides recommendations for mitigating risks, offering significant reference value for managing supply chain risks, particularly in the context of handling large amounts of dynamic data.
Authors
- Lin‐Song Cui (ORCID: https://orcid.org/0000-0001-6577-3432)
- Ning Xu (ORCID: https://orcid.org/0000-0002-0717-1713)
- Yantao Zhao
- Yang Wang (ORCID: https://orcid.org/0000-0002-5861-6081)
- Haitao Zhang (ORCID: https://orcid.org/0000-0002-2057-7654)
- Fei Wang (ORCID: https://orcid.org/0000-0002-7332-9726)
- Weiwei Han
- Feiyue Fan (ORCID: https://orcid.org/0000-0001-7230-2954)
- Jinyong Zhao
- Shengping Yao
Institutions
- Beijing University of Posts and Telecommunications (CN)
Publication Details
- Published
- 2024-12-13
- DOI
- https://doi.org/10.1109/sgei63936.2024.10914140
- Citations
- 1
- Primary Topic
- Medical Research and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.72