Network Performance

Network Performance – Development of a risk map for the inbound logistics

Client: Volkswagen Konzernlogistik

Duration: From 2015 to 2017




Project Partners


Initial Situation & Problem Setting

Car manufacturers pursue complicated supplier's networks for the procurement of required raw materials, modules and systems. These networks are characterized by nodes and edges. The suppliers form nodes of these networks, which can be characterized by criteria like cargo volume, frequency of the supply and relevance of the corresponding parts. The relations of delivery between supplier and plants of the car manufacturer can be shown as edges of the network. The car manufacturers instruct logistics providers for the realization of the transports along the edges of their networks. On this occasion, different transport models can be applied.

By the high number in degrees of freedom and the distinctive dependence of the car manufacturers on their suppliers a particular importance comes up to the consideration of herewith interlinked risks. Internal and external risks are differentiated. Internal risks can generally be supervised and influenced by the car manufacturers themselves. Internal risks are, for example, the performance of single suppliers and logistics service providers who stand in a contractual relation with the car manufacturer. However, external events cannot be influenced by the manufacturers but affect their networks. External risks are, amongst others, weather events, political crises and strikes.


Objectives & Approach

In order to reduce and supervise the possible effects of risks, an assessment methodology is developed in cooperation with the project partners for the integrated consideration of internal and external risks. A draught for the visualization of risks of supplier networks is developed to be able to show the specifically relevant information about the status of the networks to users and decision makers. The developed draughts are implemented as a software prototype of a risk map.