Automated Generation of Material Flow Network Models with Cluster Structures Using Random Walks

Abstract

In spite of the increasing digitization in manufacturing systems, the amount of publicly available data is still low. Therefore, synthetic data are frequently used in material flow simulations. In this paper, we present a new approach to generate material flow networks based on random walks. Random walks are well suited to mimic the movement of a job through a manufacturing system. By altering the parameters of a random walk the material flow can be controlled. Our aim is to show how random walks can be used to generate material flow networks with varying cluster structures as one example.