IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v66y2015i2p331-341.html
   My bibliography  Save this article

Inventory management of spare parts in an energy company

Author

Listed:
  • Mario Guajardo

    (NHH Norwegian School of Economics, Bergen, Norway)

  • Mikael Rönnqvist

    (NHH Norwegian School of Economics, Bergen, Norway)

  • Ann Mari Halvorsen

    (Statoil ASA, Sandsli, Norway)

  • Svein Inge Kallevik

    (Statoil ASA, Sandsli, Norway)

Abstract

We address the problem of how to determine control parameters for the inventory of spare parts of an energy company. The prevailing policy is based on an (s, S) system subject to a fill rate constraint. The parameters are decided based mainly on the expert judgment of the planners at different plants. The company is pursuing to conform all planners to the same approach, and to be more cost efficient. Our work focuses on supporting these goals. We test seven demand models using real-world data for about 21 000 items. We find that significant differences in cost and service level may appear from using one or another model. We propose a decision rule to select an appropriate model. Our approach allows us to recommend control parameters for 97.9% of the items. We also explore the impact of pooling inventory for different demand sources and the inaccuracy arising from duplicate item codes.

Suggested Citation

  • Mario Guajardo & Mikael Rönnqvist & Ann Mari Halvorsen & Svein Inge Kallevik, 2015. "Inventory management of spare parts in an energy company," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(2), pages 331-341, February.
  • Handle: RePEc:pal:jorsoc:v:66:y:2015:i:2:p:331-341
    as

    Download full text from publisher

    File URL: http://www.palgrave-journals.com/jors/journal/v66/n2/pdf/jors20148a.pdf
    File Function: Link to full text PDF
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: http://www.palgrave-journals.com/jors/journal/v66/n2/full/jors20148a.html
    File Function: Link to full text HTML
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Other versions of this item:

    References listed on IDEAS

    as
    1. Sridhar Bashyam & Michael C. Fu, 1998. "Optimization of (s, S) Inventory Systems with Random Lead Times and a Service Level Constraint," Management Science, INFORMS, vol. 44(12-Part-2), pages 243-256, December.
    2. Vereecke, Ann & Verstraeten, Peter, 1994. "An inventory management model for an inventory consisting of lumpy items, slow movers and fast movers," International Journal of Production Economics, Elsevier, vol. 35(1-3), pages 379-389, June.
    3. Snyder, R. D., 1984. "Inventory control with the gamma probability distribution," European Journal of Operational Research, Elsevier, vol. 17(3), pages 373-381, September.
    4. Helmut Schneider & Jeffrey L. Ringuest, 1990. "Power Approximation for Computing (s, S) Policies Using Service Level," Management Science, INFORMS, vol. 36(7), pages 822-834, July.
    5. Dekker, R. & Kleijn, M. J. & de Rooij, P. J., 1998. "A spare parts stocking policy based on equipment criticality," International Journal of Production Economics, Elsevier, vol. 56(1), pages 69-77, September.
    6. Morris A. Cohen & Paul R. Kleindorfer & Hau L. Lee, 1988. "Service Constrained (s, S) Inventory Systems with Priority Demand Classes and Lost Sales," Management Science, INFORMS, vol. 34(4), pages 482-499, April.
    7. Dunsmuir, W. T. M. & Snyder, R. N., 1989. "Control of inventories with intermittent demand," European Journal of Operational Research, Elsevier, vol. 40(1), pages 16-21, May.
    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. Olde Keizer, Minou C.A. & Teunter, Ruud H. & Veldman, Jasper, 2017. "Joint condition-based maintenance and inventory optimization for systems with multiple components," European Journal of Operational Research, Elsevier, vol. 257(1), pages 209-222.
    2. Guajardo, Mario & Rönnqvist, Mikael, 2015. "Operations research models for coalition structure in collaborative logistics," European Journal of Operational Research, Elsevier, vol. 240(1), pages 147-159.
    3. Ben Jouida, Sihem & Guajardo, Mario & Klibi, Walid & Krichen, Saoussen, 2021. "Profit maximizing coalitions with shared capacities in distribution networks," European Journal of Operational Research, Elsevier, vol. 288(2), pages 480-495.
    4. Jules Raymond Kala & Didier Michael Kre & Armelle N’Guessan Gnassou & Jean Robert Kamdjoug Kala & Yves Melaine Akpablin Akpablin & Tiorna Coulibaly, 2022. "Assets management on electrical grid using Faster-RCNN," Annals of Operations Research, Springer, vol. 308(1), pages 307-320, January.
    5. VANOVERMEIRE, Christine & CUERVO, Daniel Palhazi & SÖRENSEN, Kenneth, 2013. "Estimating collaborative profits under varying partner characteristics and strategies," Working Papers 2013031, University of Antwerp, Faculty of Business and Economics.
    6. Usman Ali & Bashir Salah & Khawar Naeem & Abdul Salam Khan & Razaullah Khan & Catalin Iulian Pruncu & Muhammad Abas & Saadat Khan, 2020. "Improved MRO Inventory Management System in Oil and Gas Company: Increased Service Level and Reduced Average Inventory Investment," Sustainability, MDPI, vol. 12(19), pages 1-19, September.
    7. Karsten, Frank & Basten, Rob J.I., 2014. "Pooling of spare parts between multiple users: How to share the benefits?," European Journal of Operational Research, Elsevier, vol. 233(1), pages 94-104.
    8. Yonit Barron & Chananel Benshimol, 2024. "Emergency Supply Alternatives for a Storage Facility of a Repairable Multi-Component System," Mathematics, MDPI, vol. 12(17), pages 1-33, August.
    9. Boliang Lin & Jiaxi Wang & Huasheng Wang & Zhongkai Wang & Jian Li & Ruixi Lin & Jie Xiao & Jianping Wu, 2017. "Inventory-transportation integrated optimization for maintenance spare parts of high-speed trains," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-18, May.
    10. Mauricio Varas & Franco Basso & Armin Lüer-Villagra & Alejandro Mac Cawley & Sergio Maturana, 2019. "Managing premium wines using an $$(s - 1,s)$$ ( s - 1 , s ) inventory policy: a heuristic solution approach," Annals of Operations Research, Springer, vol. 280(1), pages 351-376, September.
    11. Wang, Wenbin & Yue, Shuai, 2015. "An inventory pooling model for spare units of critical systems that serve multi-companies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 76(C), pages 34-44.

    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. Noordhoek, Marije & Dullaert, Wout & Lai, David S.W. & de Leeuw, Sander, 2018. "A simulation–optimization approach for a service-constrained multi-echelon distribution network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 292-311.
    2. Sandun C. Perera & Suresh P. Sethi, 2023. "A survey of stochastic inventory models with fixed costs: Optimality of (s, S) and (s, S)‐type policies—Discrete‐time case," Production and Operations Management, Production and Operations Management Society, vol. 32(1), pages 131-153, January.
    3. J J A Moors & L W G Strijbosch, 2002. "Exact fill rates for (R, s, S) inventory control with gamma distributed demand," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(11), pages 1268-1274, November.
    4. Sofia Estelles-Miguel & Manuel Cardos & Jose Miguel Albarracin Guillem & Marta Palmer Gato, 2014. "Calculation of the Approaches to Cycle Service Level in Continuous Review Policy: A Tool for Corporate Entrepreneur," Business and Management Research, Business and Management Research, Sciedu Press, vol. 3(1), pages 54-60, March.
    5. ElHafsi, Mohsen & Fang, Jianxin & Hamouda, Essia, 2021. "Optimal production and inventory control of multi-class mixed backorder and lost sales demand class models," European Journal of Operational Research, Elsevier, vol. 291(1), pages 147-161.
    6. Syntetos, Aris A. & Boylan, John E., 2006. "On the stock control performance of intermittent demand estimators," International Journal of Production Economics, Elsevier, vol. 103(1), pages 36-47, September.
    7. Cardós, Manuel & Babiloni, Eugenia, 2011. "Exact and approximated calculation of the cycle service level in a continuous review policy," International Journal of Production Economics, Elsevier, vol. 133(1), pages 251-255, September.
    8. Tamer Boyacı & Guillermo Gallego, 2002. "Managing waiting times of backordered demands in single‐stage (Q, r) inventory systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(6), pages 557-573, September.
    9. Moors, J.J.A. & Strijbosch, L.W.G., 2001. "Exact Fill Rates for (R, s, S) Inventory Control With Gamma Distributed Demand," Other publications TiSEM c967aa9c-b4fa-4074-9fbf-c, Tilburg University, School of Economics and Management.
    10. Alfieri, Arianna & Pastore, Erica & Zotteri, Giulio, 2017. "Dynamic inventory rationing: How to allocate stock according to managerial priorities. An empirical study," International Journal of Production Economics, Elsevier, vol. 189(C), pages 14-29.
    11. Karin T. Möllering & Ulrich W. Thonemann, 2008. "An optimal critical level policy for inventory systems with two demand classes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 632-642, October.
    12. Banerjee, Avijit & Burton, Jonathan & Banerjee, Snehamay, 1996. "Heuristic production triggering mechanisms under discrete unequal inventory withdrawals," International Journal of Production Economics, Elsevier, vol. 45(1-3), pages 83-90, August.
    13. 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.
    14. R. Dekker & R.M. Hill & M.J. Kleijn & R.H. Teunter, 2002. "On the (S − 1, S) lost sales inventory model with priority demand classes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(6), pages 593-610, September.
    15. Liu, Shudong & Song, Miao & Tan, Kok Choon & Zhang, Changyong, 2015. "Multi-class dynamic inventory rationing with stochastic demands and backordering," European Journal of Operational Research, Elsevier, vol. 244(1), pages 153-163.
    16. Teunter, Ruud H. & Klein Haneveld, Willem K., 2008. "Dynamic inventory rationing strategies for inventory systems with two demand classes, Poisson demand and backordering," European Journal of Operational Research, Elsevier, vol. 190(1), pages 156-178, October.
    17. Kleijnen, J.P.C. & Wan, J., 2007. "Optimization of simulated systems : OptQuest and alternatives [also see “Simulation for the optimization of (s, S) inventory system with random lead times and a service level constraint by using Arena," Other publications TiSEM ffaee312-9f6a-4452-9ccc-9, Tilburg University, School of Economics and Management.
    18. Mohammad Najjartabar Bisheh & G. Reza Nasiri & Esmaeil Esmaeili & Hamid Davoudpour & Shing I. Chang, 2022. "A new supply chain distribution network design for two classes of customers using transfer recurrent neural network," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2604-2618, October.
    19. Kleijn, M.J. & Dekker, R., 1998. "An overview of inventory systems with several demand classes," Econometric Institute Research Papers EI 9838, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Janssen, Fred & Heuts, Ruud & de Kok, Ton, 1998. "On the (R, s, Q) inventory model when demand is modelled as a compound Bernoulli process," European Journal of Operational Research, Elsevier, vol. 104(3), pages 423-436, February.

    More about this item

    JEL classification:

    • Q00 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - General
    • Q30 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - General

    Statistics

    Access and download statistics

    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:pal:jorsoc:v:66:y:2015:i:2:p:331-341. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    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.