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

汽车和机械工程行业的公司在全球分布的生产网络中运作。他们面临着对网络性能的高期望。在运营计划层面，中断会导致订单变更、质量问题和工程变更。它们对性能有负面影响。数字化可以增加信息交换，提高生产网络的透明度。公司期望更快的识别和更好的对中断的反应。然而，中断的发生、信息交换和生产网络性能之间的因果关系尚未得到研究。与此同时，令人担忧的不利成本效益比等风险阻碍了企业提高其生产网络的透明度。该研究项目的目的是增加全球生产网络的透明度。中断管理将通过增加信息交换得到改进。首先，将开发一个评估中断发生的关键绩效指标系统和一个描述信息交换特征的成熟度模型。其次是通过模拟确定中断发生、信息交换和生产网络性能之间的因果关系。为此，数学代理模型（元模型）适应模拟模型的行为。在定义了信息交换的目标状态之后，对数字化措施进行了比较，并提出了提高生产网络透明度的实施建议。本研究项目扩展了使用元模型评估和解释模拟的研究状态。汽车和机械工程行业的公司可以利用这些结果在订单管理、质量问题解决和工程变更管理三个领域改善其生产网络的性能。他们将得到支持，有针对性地选择数字化技术，以实现其生产网络的横向互联。

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.