Kenzhevayeva, Z.Katayeva, A.Kaikenova, K.Sarsembayeva, A.Babai, MZTsakalerou, M.Papadopoulos, CT.2022-02-232022-02-232021Kenzhevayeva, Z., Katayeva, A., Kaikenova, K., Sarsembayeva, A., Babai, M., Tsakalerou, M., & Papadopoulos, C. (2021). Inventory control models for spare parts in aviation logistics. Procedia Manufacturing, 55, 507–512. https://doi.org/10.1016/j.promfg.2021.10.069http://nur.nu.edu.kz/handle/123456789/6067Effective inventory management has a direct influence on monetary savings, high customer service level and product quality and thus plays an essential role in a company's economic and strategic performance. Forecasting and inventory models for aviation logistics are essential in commercial aviation. The objective of this paper is to study the problem of identifying the optimal order quantity of aircraft spare parts and the demand periods using the Order-Up-To (OUT) inventory model in conjunction with the Negative Binomial Distribution (NBD) and the (s, S) inventory model with Revised Power Approximation Method. These models are compared and contrasted via a real-world paradigm. The analysis reveals that the OUT inventory model in conjunction with the Poisson distribution allows ordering the lowest order quantity. However, the (s, S) inventory model with the Revised Power Approximation outperforms it in terms of average total inventory costs.enAttribution-NonCommercial-ShareAlike 3.0 United StatesType of access: Open Accessinventory managementAirline industryNegative Binomial distributionOrder-Up-To (OUT) inventory model(s, S) inventory modelRevised Power Approximation MethodArticle