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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Study on the Multi-level Risk Management System of Power Grid Material Supply Chain Based on Dynamic Data

Lin‐Song Cui, Ning Xu, Yantao Zhao, Yang Wang et al.
1 citations
Medical Research and Treatments
0.72
article

A Study on the Multi-level Risk Management System of Power Grid Material Supply Chain Based on Dynamic Data

Lin‐Song Cui, Ning Xu, Yantao Zhao, Yang Wang, Haitao Zhang, Fei Wang, Weiwei Han, Feiyue Fan, Jinyong Zhao, Shengping Yao
article en
1 citations

Abstract

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.

Beijing University of Posts and Telecommunications (CN)
Openalex Percentile: Top 20%
Medical Research and Treatments
0.72
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.