Methodical decision support for mid-term order planning in global production networks for multi-variant series production under uncertainty of customer order configurations

• Applicant: Professorin Dr.-Ing. Gisela Lanza
• Subject Area: Production Systems, Operations Management, Quality Management and Factory Planning
• Term: from 2017 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 393876418

The utilization of production capacities in multi-variant series production in global production networks is a challenge, but is a prerequisite for the competitive production and cost-efficient supply of customized products. Additionally, customers requiring short delivery times cause uncertainties prior to the receipt of orders regarding the balancing of customer demand with capacities of final assembly and capacities of suppliers. Thus, the uncertainty of order configurations has to be explicitly considered for robust planning in the mid-term horizon. Current planning approaches neglect either mid-term order planning at all or the consideration of uncertainties of order configurations.In order to address these shortcomings, the research proposal at hand aims at the development of a methodology to support decisions regarding mid-term order planning in global production networks for multi-variant series production under uncertainty of customer order configurations. Therefore, the type of uncertainty has to be differentiated for several industries depending on the mid-term availability of customer orders - either they are available, but their configurations are uncertain, or they are unavailable.In the case customer orders are available without certain order configurations, this uncertainty has to be considered when assigning orders in the production network. Possible configurations of customer orders have to anticipated and represented by scenarios. Thus, the customer orders can be assigned to production facilities and periods based on the results of a scenario-based optimization model.In the case of customer orders being unavailable in the mid-term horizon, uncertainty can be controlled by generating planned orders and assigning them in the production network by applying a deterministic optimization model. Later on, incoming customer orders can be assigned to the planned orders already assigned in the production network. Therefore, an optimization model can support the selection of the optimal planned order regarding configuration and delivery time. In order to enable an assignment, the selected order is to be adapted to the customer order.All in all, mid-term order planning allows for consistency between mid-term and short-term planning horizons. This cannot be guaranteed if only short-term planning is order-based. Moreover, a consistent basis of information enables integrated planning of functional units of a company such as sales, production and procurement considering their respective requirements.

• DFG Programme: Research Grants