Mathematical optimization of the tactical allocation of machining resources for an efficient capacity utilization in aerospace component manufacturing
Paper i proceeding, 2019

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.

Resource loading

Mixed Integer Linear Programming

Manufacturing

Logistics

Multi-objective optimization.

Aerospace

Capacity utilization

Optimization

Tactical resource allocation

Författare

Sunney Fotedar

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Torgny Almgren

GKN Aerospace Sweden

Stefan Cedergren

GKN Aerospace Sweden

Ann-Brith Strömberg

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Michael Patriksson

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Proceedings of the 10th Aerospace Technology Congress

1650-3686 (ISSN) 1650-3740 (eISSN)

183-188 10.3384/ecp19162021

AEROSPACE TECHNOLOGY Congress 2019. Sustainable aerospace innovation in a globalised world
Stockholm, Sweden,

Taktisk resursallokering för effektivt kapacitetsutnyttjande

VINNOVA, 2017-11-10 -- 2022-12-31.

Ämneskategorier

Produktionsteknik, arbetsvetenskap och ergonomi

Beräkningsmatematik

Annan matematik

Diskret matematik

Drivkrafter

Hållbar utveckling

Styrkeområden

Transport

Produktion

Fundament

Grundläggande vetenskaper

DOI

10.3384/ecp19162021

Mer information

Skapat

2019-10-18