Methodical decision support for dynamic allocation planning of product variants in global manufacturing networks

由于客户需求的地理变化和竞争压力的增加，使得制造企业在规划其全球制造网络时面临挑战，因此，本研究旨在支持全球制造网络中的产品变量配置决策，同时优化利用不断变化的生产环境中的生产结构和能力。由于产品变量需求的多变性，产品变量在生产阶段和生产地点的分配决策和制造网络中的配置策略决策必须同时进行。只有这样，才能适当地考虑产品变型生产需求与生产结构和能力之间的相互依赖关系。该提案解决的主要挑战是在考虑多个且不断变化的产品变型、生产阶段和多个时间段的地点时，应对计划问题的复杂性。这些变化与制造网络规划时长期且往往不可逆的决策形成对比，制造网络配置的动态可重构性和柔性度量都需要分别考虑。当产品变体的需求变化或生产环境的变化不再能通过柔性措施来补偿时，制造网络重构变得至关重要。对网络结构和容量的限制(例如生产站点的现有或潜在员工)的透明度对重新配置决策具有重要意义。基于考虑柔性度量和动态可重构性的全球制造网络优化模型，提出了一种保证后优化方法找到的解的方法。这些方法允许分析所识别的关于进一步优化潜力的最优解决方案，并说明网络配置策略对于偏离需求趋势的灵活性。

Increasing product variety due to a geographical shift of customer demand and simultaneously increasing competitive pressure pose challenges for manufacturing companies when planning their global manufacturing networks.Therefore, the presented research proposal aims at supporting product variant allocation decisions in global manufacturing networks while optimally utilizing production structures and capacities in constantly changing production environments.Due to volatile product variant demand, decisions regarding product variant allocation to production stages and sites and configuration strategy decisions in manufacturing networks have to be made simultaneously. Only in this way, interdependencies between product variant production requirements and production structures and capacities can be considered appropriately.The main challenge addressed by this proposal is to cope with planning problem complexity when considering multiple and ever-changing product variants, production stages, and sites over multiple time periods. These changes contrast long-term and often irreversible decisions when planning manufacturing networks.Both, dynamic reconfigurability and flexibility measures of manufacturing network configurations need to be considered respectively. When demand changes for product variants or changes in the production environment cannot be compensated by flexibility measures any more, manufacturing network reconfiguration becomes essential. Transparency of restricting constrains for network structures and capacities, such as existing or potential staff at production sites, is significant for reconfiguration decisions. Based on an optimization model for global manufacturing networks considering flexibility measures and dynamic reconfigurability, an approach proposed to ensure the assurance of the solution found using post optimization methods. These methods allow for analysing the identified optimal solutions regarding further optimization potential and illustrating flexibility of the network configuration strategies to deviating demand trends.