IDEAS home Printed from https://ideas.repec.org/a/eee/jaitra/v8y2002i4p221-231.html
   My bibliography  Save this article

Sources of intermittent demand for aircraft spare parts within airline operations

Author

Listed:
  • Ghobbar, A.A
  • Friend, C.H

Abstract

Owing to the sporadic nature of demand for aircraft maintenance repair parts, airline operators perceive difficulties in parts demand forecasting. In this paper we investigate the sources of demand lumpiness, as a function of flying hours, that may affect the parts demand rate. Experimental results of demand lumpiness, measured by the square coefficient of variation (CV2) and the average inter-demand interval (ADI), are examined and clarified through statistical analysis. The general linear model approach is used to explain the variation attributable to the various experimental factors and their interactions. Actual historical data for hard-time and condition-monitoring components from an airlines operator are used. This study shows that aircraft utilization rate can be a major source of lumpiness since it increases and decreases the square coefficient of variation and the average inter-demand interval respectively for the observed demand. This assumes a strictly linear relationship between demand and flying hours/landings.

Suggested Citation

  • Ghobbar, A.A & Friend, C.H, 2002. "Sources of intermittent demand for aircraft spare parts within airline operations," Journal of Air Transport Management, Elsevier, vol. 8(4), pages 221-231.
    • Handle: RePEc:eee:jaitra:v:8:y:2002:i:4:p:221-231
    DOI: 10.1016/S0969-6997(01)00054-0
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969699701000540
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/S0969-6997(01)00054-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bartezzaghi, Emilio & Verganti, Roberto & Zotteri, Giulio, 1999. "A simulation framework for forecasting uncertain lumpy demand," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 499-510, March.
    2. Christer, A. H. & Wang, W., 1995. "A simple condition monitoring model for a direct monitoring process," European Journal of Operational Research, Elsevier, vol. 82(2), pages 258-269, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gu, Jingyao & Zhang, Guoqing & Li, Kevin W., 2015. "Efficient aircraft spare parts inventory management under demand uncertainty," Journal of Air Transport Management, Elsevier, vol. 42(C), pages 101-109.
    2. Nenes, George & Panagiotidou, Sofia & Tagaras, George, 2010. "Inventory management of multiple items with irregular demand: A case study," European Journal of Operational Research, Elsevier, vol. 205(2), pages 313-324, September.
    3. Gutierrez, Rafael S. & Solis, Adriano O. & Mukhopadhyay, Somnath, 2008. "Lumpy demand forecasting using neural networks," International Journal of Production Economics, Elsevier, vol. 111(2), pages 409-420, February.
    4. Fabian Taigel & Anselme K. Tueno & Richard Pibernik, 2018. "Privacy-preserving condition-based forecasting using machine learning," Journal of Business Economics, Springer, vol. 88(5), pages 563-592, July.
    5. Teunter, Ruud H. & Syntetos, Aris A. & Zied Babai, M., 2011. "Intermittent demand: Linking forecasting to inventory obsolescence," European Journal of Operational Research, Elsevier, vol. 214(3), pages 606-615, November.
    6. Regattieri, A. & Giazzi, A. & Gamberi, M. & Gamberini, R., 2015. "An innovative method to optimize the maintenance policies in an aircraft: General framework and case study," Journal of Air Transport Management, Elsevier, vol. 44, pages 8-20.
    7. Aysun Kapucugil Ikiz & Gizem Halil Utma, 2023. "Combined Forecasts of Intermittent Demand for Stock-keeping Units (SKUs)," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 9(1), pages 1-31, June.
    8. Yongquan, Sun & Xi, Chen & He, Ren & Yingchao, Jin & Quanwu, Liu, 2016. "Ordering decision-making methods on spare parts for a new aircraft fleet based on a two-sample prediction," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 40-50.
    9. Dinis, Duarte & Barbosa-Póvoa, Ana & Teixeira, Ângelo Palos, 2019. "A supporting framework for maintenance capacity planning and scheduling: Development and application in the aircraft MRO industry," International Journal of Production Economics, Elsevier, vol. 218(C), pages 1-15.
    10. Regattieri, A. & Gamberi, M. & Gamberini, R. & Manzini, R., 2005. "Managing lumpy demand for aircraft spare parts," Journal of Air Transport Management, Elsevier, vol. 11(6), pages 426-431.
    11. Pinçe, Çerağ & Turrini, Laura & Meissner, Joern, 2021. "Intermittent demand forecasting for spare parts: A Critical review," Omega, Elsevier, vol. 105(C).
    12. Syntetos, Aris A., 2007. "A note on managing lumpy demand for aircraft spare parts," Journal of Air Transport Management, Elsevier, vol. 13(3), pages 166-167.
    13. Babai, Zied & Boylan, John E. & Kolassa, Stephan & Nikolopoulos, Konstantinos, 2016. "Supply chain forecasting: Theory, practice, their gap and the futureAuthor-Name: Syntetos, Aris A," European Journal of Operational Research, Elsevier, vol. 252(1), pages 1-26.
    14. Dhanisetty, V.S. Viswanath & Verhagen, W.J.C. & Curran, Richard, 2018. "Multi-criteria weighted decision making for operational maintenance processes," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 152-164.
    15. Van der Auweraer, Sarah & Boute, Robert N. & Syntetos, Aris A., 2019. "Forecasting spare part demand with installed base information: A review," International Journal of Forecasting, Elsevier, vol. 35(1), pages 181-196.
    16. Costantino, Francesco & Di Gravio, Giulio & Patriarca, Riccardo & Petrella, Lea, 2018. "Spare parts management for irregular demand items," Omega, Elsevier, vol. 81(C), pages 57-66.
    17. Moon, Seongmin & Hicks, Christian & Simpson, Andrew, 2012. "The development of a hierarchical forecasting method for predicting spare parts demand in the South Korean Navy—A case study," International Journal of Production Economics, Elsevier, vol. 140(2), pages 794-802.
    18. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
    19. A A Syntetos & M Z Babai & Y Dallery & R Teunter, 2009. "Periodic control of intermittent demand items: theory and empirical analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(5), pages 611-618, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guo R. & Ascher H. & Love E., 2001. "Towards Practical and Synthetical Modelling of Repairable Systems," Stochastics and Quality Control, De Gruyter, vol. 16(1), pages 147-182, January.
    2. Bae, Suk Joo & Mun, Byeong Min & Chang, Woojin & Vidakovic, Brani, 2019. "Condition monitoring of a steam turbine generator using wavelet spectrum based control chart," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 13-20.
    3. Bartezzaghi, Emilio & Verganti, Roberto & Zotteri, Giulio, 1999. "Measuring the impact of asymmetric demand distributions on inventories," International Journal of Production Economics, Elsevier, vol. 60(1), pages 395-404, April.
    4. Zotteri, Giulio & Verganti, Roberto, 2001. "Multi-level approaches to demand management in complex environments: an analytical model," International Journal of Production Economics, Elsevier, vol. 71(1-3), pages 221-233, May.
    5. Pinciroli, Luca & Baraldi, Piero & Compare, Michele & Zio, Enrico, 2023. "Optimal operation and maintenance of energy storage systems in grid-connected microgrids by deep reinforcement learning," Applied Energy, Elsevier, vol. 352(C).
    6. Dieulle, L. & Berenguer, C. & Grall, A. & Roussignol, M., 2003. "Sequential condition-based maintenance scheduling for a deteriorating system," European Journal of Operational Research, Elsevier, vol. 150(2), pages 451-461, October.
    7. Danese, Pamela & Kalchschmidt, Matteo, 2011. "The impact of forecasting on companies' performance: Analysis in a multivariate setting," International Journal of Production Economics, Elsevier, vol. 133(1), pages 458-469, September.
    8. Murphy Choy & Michelle L. F. Cheong, 2011. "Identification of Demand through Statistical Distribution Modeling for Improved Demand Forecasting," Papers 1110.0062, arXiv.org.
    9. Jože Martin Rožanec & Blaž Fortuna & Dunja Mladenić, 2022. "Reframing Demand Forecasting: A Two-Fold Approach for Lumpy and Intermittent Demand," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
    10. Percy, David F. & Kobbacy, Khairy A. H., 2000. "Determining economical maintenance intervals," International Journal of Production Economics, Elsevier, vol. 67(1), pages 87-94, August.
    11. Ponchet, Amélie & Fouladirad, Mitra & Grall, Antoine, 2010. "Assessment of a maintenance model for a multi-deteriorating mode system," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1244-1254.
    12. Bacchetti, Andrea & Saccani, Nicola, 2012. "Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice," Omega, Elsevier, vol. 40(6), pages 722-737.
    13. Erick Sager & Olga A. Timoshenko, 2021. "Demand Uncertainty, Selection, and Trade," DETU Working Papers 2104, Department of Economics, Temple University.
    14. Fauriat, William & Zio, Enrico, 2020. "Optimization of an aperiodic sequential inspection and condition-based maintenance policy driven by value of information," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    15. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    16. Pujawan, I. Nyoman & Kingsman, Brian G., 2003. "Properties of lot-sizing rules under lumpy demand," International Journal of Production Economics, Elsevier, vol. 81(1), pages 295-307, January.
    17. Muñoz Negrón, David F. & Muñoz Medina, Diego F., 2009. "Bayesian Forecastings For Automobile Parts Using Stochastic Simulation," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 14(27), pages 7-20.
    18. Wang, W. & Zhang, W., 2008. "An asset residual life prediction model based on expert judgments," European Journal of Operational Research, Elsevier, vol. 188(2), pages 496-505, July.
    19. Wang, Ling & Chu, Jian & Mao, Weijie, 2009. "A condition-based replacement and spare provisioning policy for deteriorating systems with uncertain deterioration to failure," European Journal of Operational Research, Elsevier, vol. 194(1), pages 184-205, April.
    20. Pedregal, Diego J. & Carmen Carnero, Ma., 2009. "Vibration analysis diagnostics by continuous-time models: A case study," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 244-253.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jaitra:v:8:y:2002:i:4:p:221-231. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/journal-of-air-transport-management/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.