Initial provisioning and spare parts inventory network optimisation in a multi maintenance base environment

Abstract

Aviation spare parts provisioning is a highly complex problem. Traditionally, provisioning has been carried out using a conventional Poisson-based approach where inventory quantities are calculated separately for each part number and demands from different operations bases are consolidated into one single location. In an environment with multiple operations bases, however, such simplifications can lead to situations in which spares -although available at another airport -first have to be shipped to the location where the demand actually arose, leading to flight delays and cancellations. In this paper we demonstrate how simulation-based optimisation can help with the multi-location inventory problem by quantifying synergy potential between locations and how total service lifecycle cost can be further reduced without increasing risk right away from the Initial Provisioning (IP) stage onwards by taking into account advanced logistics policies such as pro-active re-balancing of spares between stocking locations.

Simulation-based Modeling for Min/Max Ordering Policy for Repairable Items Inventory Systems

“…Very few researchers have developed exact simulation models, which can be deployed for use in repairable items inventory management. (Lye et al, 2008), (Nie and Sheng, 2009), (Kilpi et al, 2008), Lendermann, et al, 2012, (Li et al, 2017).…”

Linking the spare parts management with the total costs of ownership: An agenda for future research

“…In Yang and Du (2004) an evaluation method to facilitate the initial provisioning of the critical spare parts that have significant impacts on the operational availability and total life-cycle cost is proposed. Lendermann, Thirunavukkarasu, Low and McGinnis (2012) applied simulation-based optimization to a multi-location inventory problem and demonstrated how total service lifecycle cost can be reduced without increasing risk promptly from the Initial Provisioning stage by putting into practice proper logistics policies.…”

An innovative method to optimize the maintenance policies in an aircraft: General framework and case study

“…Lee et al (2008) develop a solution framework that integrates a multi-objective evolutionary algorithm (MOEA) with the multi-objective computing budget allocation (MOCBA) method for the multi-objective simulation optimization problem applied to the aircraft spare parts allocation problem. Lendermann et al (2012) investigate the multilocation inventory problem by quantifying synergy potential between locations. They also discuss how the total service lifecycle cost can be further reduced without increasing risk right away from the initial provisioning (IP) stage onwards by taking into account advanced logistics policies such as pro-active re-balancing of spares between stocking locations.…”