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Robust assignment of customer orders with uncertain configurations in a production network for aircraft manufacturing

Buergin, J., Blaettchen, P. ORCID: 0000-0002-4253-6079, Kronenbitter, J. , Molzahn, K., Schweizer, Y., Strunz, C., Almagro, M., Bitte, F., Ruehr, S., Urgo, M. & Lanza, G. (2019). Robust assignment of customer orders with uncertain configurations in a production network for aircraft manufacturing. International Journal of Production Research, 57(3), pp. 749-763. doi: 10.1080/00207543.2018.1482018

Abstract

Production of multi-variant products in a network requires the assignment of customer orders to locations and periods. This is a highly complex planning task, as requirements of procurement, production, distribution, and sales have to be considered. Providing customers with the flexibility of configuring their ordered products after order assignment further increases the complexity of the planning task by taking uncertainty into account. Therefore, a robust optimisation model, using scenarios representing potential customer-specific order configurations, is introduced. By providing enough flexibility to handle maximum work overload caused by the potential order configurations at locations, a robust assignment of orders can be guaranteed in order to avoid undesirable situations causing delays and additional costs. Therefore, the mid-term adjustments of the flexibility limits are enabled by the changeability of workforce supply by making use of external workers. An industrial application of the model in manufacturing of the Airbus A320 Family of aircrafts is presented. The costs for offering configuration flexibility to customers are quantified by the expected value of perfect information. The explicit consideration of configuration uncertainty through the use of scenarios is discussed based on the value of the stochastic solution in comparison to the results attained by simplistically using the expected value.

Publication Type: Article
Additional Information: Robust optimisation, production planning, manufacturing networks, uncertainty
Subjects: H Social Sciences > HD Industries. Land use. Labor
H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Departments: Bayes Business School > Management
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