Migration planning of global production networks – methodological support for the determination of robust migration paths and risk-efficient enablers of change

今天的生产网络往往是不协调的决策和机会主义发展的结果。因此，制造企业经常在复杂、低效和僵化的网络中生产，缺乏战略重点。与此同时，现代全球化给企业带来了商业环境的颠覆性变化以及日益激烈的竞争和成本压力。出于这个原因，制造公司必须迁移其历史上增长的生产网络，因此，不断调整网络配置以适应不断变化的条件。本建议的目标是为全球生产网络的迁移规划开发一种基于模型的方法。在制定重点突出的全球生产战略的基础上（该战略必须支持公司的竞争战略），必须在考虑到商业环境的不稳定影响因素的情况下确定网络配置的迁移路径，并必须为网络对象创造适当程度的可变性。为了实现这一目标，将形式化全球生产网络的结构和对象的建模和优化的客观数学模型。首先，将开发一个基于资源的网络模型，使不同的网络配置形式化。应用该模型，将推导出实现全球生产策略的配置。生成的配置将集成到一个随机动态优化模型中，以便确定网络配置的最佳迁移策略/策略。此外，商业环境变化的驱动因素将被参数化并集成为随机模型参数。最后，将开发一个随机决策模型，该模型能够为网络对象选择具有风险效率的变化推动者，从而使其能够在规划范围内的每个规划期间进行主动准备。开发的模型将在案例研究中进行测试和验证。

Today’s production networks are often the result of uncoordinated decisions and opportunistic developments over time. Hence, manufacturing companies very often produce in complex, inefficient and rigid networks lacking strategical focus. Simultaneously, modern globalization challenges companies with disruptive changes of the business environment as well as increasing competition and cost pressure. For this reason, manufacturing companies must migrate their historical grown production networks and, therefore, continuously adapt the network configuration to changing conditions.The objective of this proposal is the development of a model based methodology for migration planning of global production networks. Based on the formulation of a focused global production strategy, which has to support the competitive strategy of a company, migration paths of the network configuration have to be identified under consideration of volatile influencing factors of the business environment and an adequate level of changeability for network objects has to be created.To achieve this, objective mathematical models for modelling and optimization of the structure and objects of a global production network will be formalized. Firstly, a resource based network model that enables the formalization of different network configurations will be developed. Applying this model, configurations which operationalize a global production strategy will be derived. The resulting configurations will be integrated into a stochastic-dynamic optimization model in order to identify an optimal migration strategy/policy of the network configuration. Furthermore, drivers of change of the business environment will be parametrized and integrated as stochastic model parameters. Lastly, a stochastic decision model will be developed which enables the selection of risk-efficient enablers of change for the network objects to enable their pro-active preparation for each planning period in the planning horizon. The developed models will be tested and validated in case studies.