Performance measures of nonstationary inventory models for perishable products under the EWA policy
Accurately estimating key performance indicators in inventory models for perishable items is essential in order to assess and improve the management strategy of these systems. We analyse the production of platelet concentrates at blood banks under the EWA replenishment policy. We give analytical app...
| Authors: | , , |
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| Format: | article |
| Publication Date: | 2022 |
| Country: | España |
| Institution: | Universidad del País Vasco |
| Repository: | Addi. Archivo Digital para la Docencia y la Investigación |
| OAI Identifier: | oai:addi.ehu.eus:10810/59369 |
| Online Access: | http://hdl.handle.net/10810/59369 |
| Access Level: | Open access |
| Keyword: | inventory perishable periodic review stochastic demand platelets |
| Summary: | Accurately estimating key performance indicators in inventory models for perishable items is essential in order to assess and improve the management strategy of these systems. We analyse the production of platelet concentrates at blood banks under the EWA replenishment policy. We give analytical approximations of the most important performance measures, such as the size of orders, the size of stocks, the percentage of outdating, the age distribution of stocks and the freshness of units issued, among others. The production of platelet concentrates is a prototypical example of inventory models for short life items with random demand and a weekly pattern, where a high service level is required. The methodology and the approximations presented here can be easily adapted to other inventory systems with similar characteristics. Most of the formulae in this article are new for nonstationary models under the EWA policy; indeed, formulae for the age distribution of units in stock and of units issued have not appeared in the literature even for the simpler base-stock replenishment policy. We apply our results to a real blood bank and find very close agreement between the formulae and the results of Monte Carlo simulations. The accuracy of our approximations is also tested in several scenarios, depending on the lifetime of units, safety stock levels and the probabilistic distribution of demand. |
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