Transparency in Global Production Networks: Improving Disruption Management by Increased Information Exchange

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Companies in the automotive and mechanical engineering industry operate in globally distributed production networks. They are confronted with high expectations regarding the performance of their networks. At the operational planning level, disruptions result in order changes, quality problems and engineering changes. They have a negative impact on the performance. Digitalization enables an increased exchange of information and an increase in transparency in production networks. Companies expect a faster identification and a better response to disruptions. However, the cause-effect relationships between the occurrence of disruptions, the exchange of information and the performance of the production networks have not yet been researched. At the same time, risks such as a feared unfavourable cost-benefit ratio prevent companies from increasing the transparency of their production networks.The aim of the research project is to increase the transparency of global production networks. Disruption management is to be improved by an increased information exchange. First, a key performance indicator system for evaluating the occurrence of disruptions and a maturity model for characterising the information exchange will be developed. This is followed by the determination of cause-effect relationships between the occurrence of disruptions, the exchange of information and the performance of production networks by simulation. For this purpose, mathematical surrogate models (metamodels) are adapted to the behaviour of the simulation model. After defining a target state for the information exchange, a comparison of digitalization measures and the recommendation of their implementation to increase transparency in the production network follow.This research project extends the state of research in the evaluation and interpretation of simulation using metamodels. Companies in the automotive and mechanical engineering industry can use the results to improve the performance of their production networks in the three areas of order management, quality problem solving and engineering change management. They will be supported in the targeted selection of digitalization technologies for a horizontal interlinkage of their production networks.