Spare Parts Inventory Planning In The Aircraft MRO Industry By Integrating Demand Categorization And The RPA (s,S) Policy Method

Authors

  • Raga C. A. Pambudi Department of Industrial Engineering, Faculty of Engineering, Universitas Indonesia,Indonesia
  • Yuri M. Zagloel Department of Industrial Engineering, Faculty of Engineering, Universitas Indonesia,Indonesia

DOI:

https://doi.org/10.51601/ijse.v6i2.598

Abstract

Air transportation in Indonesia has experienced significant growth in passenger traffic over the past few years, driven by factors such as travel distance, time efficiency, safety, and service quality. From a safety perspective, one critical aspect that must not be overlooked is the availability of spare parts during Maintenance, Repair, and Overhaul (MRO) activities, as it directly affects aircraft airworthiness and flight safety. Demand for spare parts in the MRO industry is influenced by maintenance schedules and aircraft utilization, resulting in varying demand patterns characterized by different levels of demand variability and demand frequency. This study focuses on inventory planning in an Indonesian aircraft MRO company using the Revised Power Approximation (RPA) (s,S) policy. The proposed inventory policy is evaluated by comparing its performance with the company's existing inventory management approach in terms of total inventory cost and customer service level. The results demonstrate that the RPA (s,S) policy can effectively reduce inventory-related costs and improve service performance, thereby enhancing spare parts availability to support maintenance operations and flight safety.

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References

[1] Babiloni, E., & Guijarro, E. (2018). Fill rate: From its definition to its calculation for the continuous inventory system with discrete demands and lost sales. Central European Journal of Operations Research, 28(1), 351–363. https://doi.org/10.1007/s10100-018-0546-7

[2] Bijvank, M., & Vis, I. F. A. (2011). Lost-sales inventory theory: A review. European Journal of Operational Research, 215(1), 1–13.https://doi.org/10.1016/j.ejor.2011.02.004

[3] Ehrhardt, R. (1979). The power approximation for computing (s, S) inventory policies. Management Science, 25(8), 777–78

[4] Ehrhardt, R., & Mosier, C. (1984). A revision of the power approximation for computing (s, S) policies. Management Science, 30(5), 618–622.

[5] Ghobbar, A. A., & Friend, C. H. (2002). Sources of intermittent demand for aircraft spare parts within airline operations. Journal of Air Transport Management, 8(6), 429–439. https://doi.org/10.1016/S0969-6997(02)00015-7

[6] International Air Transport Association. (2015). Guidance material and best practices for inventory management, 2nd Edition.

[7] Jiang, P., Huang, Y., & Liu, X. (2021). Intermittent demand forecasting for spare part in the heavy-duty vehicle industry: A support vector machine model. International Journal of Production Research, 59(24), 7423–7440. https://doi.org/10.1080/00207543.2020.1842936

[8] Kaya, G. O., Şahin, M., & Demirel, O. F. (2020). Intermittent demand forecasting: A guideline for method selection. Sadhana, 45(51), 1–7. https://doi.org/10.1007/s12046-020-1285-8

[9] Kiefer, D., Grimm, F., Bauer, M., & van Dinther, C. (2021). Demand forecasting intermittent and lumpy time series: Comparing statistical, machine learning and deep learning methods. In Proceedings of the 54th Hawaii International Conference on System Sciences (HICSS-54) (pp. 1425-1432). https://doi.org/10.24251/HICSS.2021.172

[10] Kenzhevayeva, Z., Katayeva, A., Kaikenova, K., Sarsembayeva, A., Babai, M. Z., Tsakalerou, M., & Papadopoulos, C. T. (2021). Inventory control models for spare part in aviation logistics. Procedia Manufacturing, 55, 507–512. https://doi.org/10.1016/j.promfg.2021.10.069

[11] Lam, C. Y., & Ip, W. H. (2010). A customer satisfaction inventory model for supply chain integration. Expert Systems with Applications, 37(1), 769–775. https://doi.org/10.1016/j.eswa.2009.06.073

[12] National Aviation Academy. (2023). The different types of aviation maintenance checks. https://www.naa.edu/types-of-aviation-maintenance-checks

[13] Sahin, M., Eldemir, F., & Turkyilmaz, A. (2021). Inventory cost minimization of spare part in aviation industry. Transportation Research Procedia, 59, 29–37. https://doi.org/10.1016/j.trpro.2021.11.094

[14] Syntetos, A. A., Boylan, J. E., & Croston, J. D. (2005). On the categorization of demand patterns. Journal of the Operational Research Society, 56(5), 495–503. https://doi.org/10.1057/palgrave.jors.2601841

[15] Tian, X., Wang, H., & E, E. (2021). Forecasting intermittent demand for inventory management by retailers: A new approach. Journal of Retailing and Consumer Services, 62, 102662. https://doi.org/10.1016/j.jretconser.2021.102662

[16] Zhu, H., Liu, X., & Chen, Y. (Frank). (2015). Effective inventory control policies with a minimum order quantity and batch ordering. International Journal of Production Economics, 168, 21–30. https://doi.org/10.1016/j.ijpe.2015.06.008.

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Published

2026-06-06

How to Cite

Raga C. A. Pambudi, & Yuri M. Zagloel. (2026). Spare Parts Inventory Planning In The Aircraft MRO Industry By Integrating Demand Categorization And The RPA (s,S) Policy Method. International Journal of Science and Environment (IJSE), 6(2), 1303–1310. https://doi.org/10.51601/ijse.v6i2.598

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