Inventory control models for spare parts in aviation logistics

Z. Kenzhevayeva, A. Katayeva, K. Kaikenova, A. Sarsembayeva, M. Z. Babai, M. Tsakalerou, Chrysoleon Papadopoulos

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)


Effective 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.

Original languageEnglish
Pages (from-to)507-512
Number of pages6
JournalProcedia Manufacturing
Issue numberC
Publication statusPublished - 2021
Event30th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2021 - Athens, Greece
Duration: Sept 7 2021Sept 10 2021


  • (s, S) inventory model
  • Airline industry
  • Inventory management
  • Negative Binomial distribution
  • Order-Up-To (OUT) inventory model
  • Revised Power Approximation Method

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence


Dive into the research topics of 'Inventory control models for spare parts in aviation logistics'. Together they form a unique fingerprint.

Cite this