Abstract
The manufacturing industry is characterized by large-scale interdependent networks as companies buy goods from one another, but do not control or design the overall flow of materials. The result is a complex emergent structure with which companies connect to each other. The topology of this structure impacts the industry’s robustness to disruptions in companies, countries, and regions. In this work, we propose an analysis framework for examining robustness in the manufacturing industry and validate it using an empirical dataset. Focusing on two key angles, suppliers and products, we highlight macroscopic and microscopic characteristics of the network and shed light on vulnerabilities of the system. It is shown that large-scale data on structural interdependencies can be examined with measures based on network science.
Highlights
Introduction and backgroundA supply network is created when companies buy and sell goods to each other, transferring necessary parts downstream to create a final product
We propose an analysis framework for examining robustness in the manufacturing industry and validate it using an empirical dataset
Modularity can point to the extent where failures can be contained within communities The shorter the average path length, the more efficient the flow of materials The higher the clustering coefficient, the more dependent suppliers are on each other for production Integrators that assemble components Supply load Demand load The speed with which information and material can be disseminated in the network and suppliers that act as bottlenecks during disruptions Speed with which disruptions from a disrupted node can affect others A homogeneous distribution shows most suppliers have similar numbers of products, affecting the overall assembly in similar way Companies with large numbers of product types would have a higher impact on the network than companies with small numbers of product types
Summary
A supply network is created when companies buy and sell goods to each other, transferring necessary parts downstream to create a final product. Companies do not have visibility beyond their immediate buyers and suppliers, which results that these networks are not designed but emerge [10] These networks can become large scale, with many thousands of companies becoming interdependent without their knowledge of being so. Global automotive production dropped by one-third, resulting in an overall loss of 5 million vehicles worldwide, out of the 72 million planned for 2011 (*7 % loss) Both in terms of risk management for the entire network, and from the perspective of individual firms planning and coordinating with different suppliers, a better understanding of interdependencies would help create better strategies for robustness. The field of supply chain planning has a long history of creating sophisticated operational models that describe the flow of materials between organizations. In the context of robustness to failures, several inventory and optimization
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