Simulation-based analysis of inventory levels for low demand spare parts in a cooperative inventory pooling-system

  • Yannic Hafner  , 
  • b Christian Looschen  , 
  • c Johannes Fottner  
  • abc Technical University of Munich, Germany
Cite as
Hafner Y., Looschen C., Fottner J. (2019). Simulation-based analysis of inventory levels for low demand spare parts in a cooperative inventory pooling-system. Proceedings of the 18th International Conference on Modelling and Applied Simulation (MAS 2019), pp. 72-78. DOI: https://doi.org/10.46354/i3m.2019.mas.010
 Download PDF

Abstract

Due to their systemic relevance, a high availability of intralogistics systems is crucial. This requires the stockpiling of capital-intensive spare parts. Strategies are therefore needed to reduce the severe capital commitment for spare parts management. No practical recommendations and solutions for this problem are available however. This contribution describes strategies and procedures for a cooperative inventory poolingsystem and our model of a simulation-based analysis of inventory levels for low demand spare parts in these systems. We determine that companies can gain benefits and greatly lower their inventory level and associated costs when cooperating in spare parts management. Furthermore, we investigated effects of changing network compositions while cooperating over time.

References

  1. Fritzsche R., 2012. Cost adjustment for single item pooling models using a dynamic failure rate: A calculation for the aircraft industry. Transportation Research Part E 48, pp. 1065-1079.
  2. Gallagher T., Mitchke M. D., Rogers M C, 2005. Profiting from spare parts. The McKinsey Quaterly.
  3. Huiskonen J., 2001. Maintenance spare parts logistics. Special characteristics and strategic choices. International Journal of Production Economics 71 (1-3), S. 125–133.
  4. Karsten F., Basten R., 2014. Pooling of spare parts between multiple users. How to share the benefits? European Journal of Operational Research (233-1), S. 94–104.
  5. Kukreja A., Schmidt C. P., Miller D. M., 2001. Stocking Decisions for Low-Usage Items in a Multilocation Inventory System. Management Science 47 (10), S. 1371–1383.
  6. Paterson C., Kiesmuller G. P., Teunter R. H., Glazebrook K., 2009. Inventory models with lateral
    transshipments: a review. Eindhoven University of Technology.
  7. Schillinger R., Wortmann B., Buß D., 2015. Ressourcenschonende Chemieparklogistik. In: Voß P., 2015, eds. Logistik – eine Industrie, die (sich) bewegt, Wießbaden, pp. 173 -190.
  8. Shen Z. M., Coullard C., Daskin M. S., 2003. A joint Location-Invenotry Model. Transportation Science 37(1), pp. 40-55.
  9. Verein Deutscher Ingenieure (VDI), 2014. VDI-3633 Part 1: Simulation of systems in materials handling, logistics and production – Fundamentals. Beuth Verlag, Berlin.
  10. Wang W., 2012. A stochastic model for joint spare parts inventory and planned maintenance optimisation. EURO Excellence in Practice Award 2001 216 (1), S. 127–139.
  11. Wong H., Cattrysse D., Van Oudheusden D, 2004. Inventory pooling of repairable spare parts with non-zero lateral transshipment time and delayed lateral transshipment, European Journal of Operation Research (165), pp- 207-218.