Below is a simple graphical representation of a spare parts supply chain.
Currently there is a centralized spare part inventory where ROP is calculated based on outgoing demand. SS= normsinv(0.99)*Stdeviation* Sqrt(Lead time demand + review period).
Since this is only assuming the variability in outgoing demand, it does not actually consider the variability in demand from the service centres. In the future I would like to decrease the safety stock required by considering local DC variability in demand, but there is a problem I need to solve first:
The spare part demand for majority of spare parts is not normally distributed, so the z-score currently used does not seem to be reliable. This is further backed up by the fact that the spare part availability is between 85% to 87% at the service centres.
Are there any substitutes or ways to calculate safety stock when the demand is not normally distributed? for instance, alternative to z-score?
best regards,
Janis
In that case you may assume stochastic demand. Check these works:
https://tandfonline.com/doi/abs/10.1080/09537287.2015.1033497?src=recsys&journalCode=tppc20
Article DATA ANALYSIS FOR INVENTORY MANAGEMENT IN A MULTI-ECHELON SUPPLY CHAIN
Dear Janis,
That is certainly a challenging topic.
You may find the following papers/websites interesting.
Deleted research item The research item mentioned here has been deleted
https://pkg.robjhyndman.com/forecast/reference/croston.html
https://www.logistiek.nl/supply-chain/blog/2009/09/voorraadniveau-bepalen-bij-onregelmatige-vraag-101131771
https://smartcorp.com/wp-content/uploads/2015/08/Bootstrap_Article.pdf
Good luck!
Hello,
Concerning spare parts inventory management, I advise you to read the following articles, about MRO (Maintenance, Repair & Overhaul): (1) https://www.mro-network.com/maintenance-repair-overhaul/aircraft-spare-parts-pooling-art-or-science ; (2) https://www.mro-network.com/components/spare-parts-inventory-management.
Best regards
if the spare value is make to stock and not make to order, it is better to visualise the past data and go for periodic replenishment with a fixed order point considering the lead time.
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