Sunney Fotedar
Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
Torgny Almgren
Logistics, GKN Aerospace, Trollhättan, Sweden
Stefan Cedergren
PTC, GKN Aerospace, Trollhättan, Sweden
Ann-Brith Strömberg
Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
Michael Patriksson
Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
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http://dx.doi.org/10.3384/ecp19162021Published in: FT2019. Proceedings of the 10th Aerospace Technology Congress, October 8-9, 2019, Stockholm, Sweden
Linköping Electronic Conference Proceedings 162:21, p. 183-188
Published: 2019-10-23
ISBN: 978-91-7519-006-8
ISSN: 1650-3686 (print), 1650-3740 (online)
In the aerospace industry, with low volumes and many products, there is a critical need to efficiently use available manufacturing resources. Currently, at GKN Aerospace, resource allocation decisions that in many cases will last for several years are to some extent made with a short-term focus so as to minimize machining time, which results in a too high load on the most capable machines, and too low load on the less capable ones. This creates an imbalance in capacity utilization that leads to unnecessary queuing at some machines, resulting in long lead times and in an increase in tied-up capital. Tactical resource allocation on the medium to long-range planning horizon (six months to several years) aims to address this issue by allocating resources to meet the predicted future demand as effectively as possible, in order to ensure long range profitability. Our intent is to use mathematical optimization to find the best possible allocations.
tactical resource allocation, capacity utilization, mixed integer linear programming, manufacturing, resource loading, logistics
Aerospace
