On perishable inventory in healthcare: Random expiration dates and age discriminated demand
On perishable inventory in healthcare: Random expiration dates and age discriminated demand
The management of perishable inventories is particularly challenging in healthcare field. One of the reasons lashing this is volatility, which is driven by irregular supply and stochastic demand. Exacerbated by a number of other factors such as the relatively short products shelf life, accelerated degradation and deterioration (premature expiration) and user specificity, such irregular supply and stochastic demand of perishable inventories bring additional challenges to the delivery of health services. This variability is likely to expose not only those in direct receipt of such healthcare products, but also the general population to insecure supplies. The norm in perishable products is to set an expiration date by which the product is best consumed. However, deterioration in products may accelerate, thereby; causing products to expire prematurely in random before their anticipated expiration date.
With this in mind, the aim of the study is to explore how best to mitigate against inventory volatility in perishable inventory, which is characterized by random premature expiration, random demand, irregular supply, age differentiated demand and custom replenishment guidelines. Through the adoption of simulation-optimization along with new settings and replenishment policies, the optimized quantity level of daily orders could be determined for this combination of inventory restrictions. Owed to their custom medical compatibility guidelines, and their notable accelerated expiration, blood platelets were considered here. As study outcome, the emergent model presents a perspective of supply chains and their healthcare imperatives that will enable healthcare supply chain managers not only to discern, but also to interpret and facilitate the management and implementation of optimal inventories.
Random Aging; Differentiated Demand; Perishable Inventory; Blood Platelets; Simulation; Optimization.
1-22
Dalalah, Doraid
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Ojiako, Udechukwu
39f57398-8b7b-422c-9186-6a87c75e0f8f
Chipulu, Maxwell
12545803-0d1f-4a37-b2d2-f0d21165205e
Dalalah, Doraid
b6dc77ef-a996-4173-a303-ffb6c17214d3
Ojiako, Udechukwu
39f57398-8b7b-422c-9186-6a87c75e0f8f
Chipulu, Maxwell
12545803-0d1f-4a37-b2d2-f0d21165205e
Dalalah, Doraid, Ojiako, Udechukwu and Chipulu, Maxwell
(2020)
On perishable inventory in healthcare: Random expiration dates and age discriminated demand.
Journal of Simulation, .
(doi:10.1080/17477778.2020.1851614).
Abstract
The management of perishable inventories is particularly challenging in healthcare field. One of the reasons lashing this is volatility, which is driven by irregular supply and stochastic demand. Exacerbated by a number of other factors such as the relatively short products shelf life, accelerated degradation and deterioration (premature expiration) and user specificity, such irregular supply and stochastic demand of perishable inventories bring additional challenges to the delivery of health services. This variability is likely to expose not only those in direct receipt of such healthcare products, but also the general population to insecure supplies. The norm in perishable products is to set an expiration date by which the product is best consumed. However, deterioration in products may accelerate, thereby; causing products to expire prematurely in random before their anticipated expiration date.
With this in mind, the aim of the study is to explore how best to mitigate against inventory volatility in perishable inventory, which is characterized by random premature expiration, random demand, irregular supply, age differentiated demand and custom replenishment guidelines. Through the adoption of simulation-optimization along with new settings and replenishment policies, the optimized quantity level of daily orders could be determined for this combination of inventory restrictions. Owed to their custom medical compatibility guidelines, and their notable accelerated expiration, blood platelets were considered here. As study outcome, the emergent model presents a perspective of supply chains and their healthcare imperatives that will enable healthcare supply chain managers not only to discern, but also to interpret and facilitate the management and implementation of optimal inventories.
Text
Dalalah et al 2020 Managing perishable inventories in healthcare services. Journal of Simulation, Accepted for publication. Journal of Simulation, Accepted for publication
- Accepted Manuscript
More information
Accepted/In Press date: 10 November 2020
e-pub ahead of print date: 21 December 2020
Keywords:
Random Aging; Differentiated Demand; Perishable Inventory; Blood Platelets; Simulation; Optimization.
Identifiers
Local EPrints ID: 445085
URI: http://eprints.soton.ac.uk/id/eprint/445085
ISSN: 1747-7778
PURE UUID: ec863e05-b1ce-4d3f-bfdf-f8369070ad2f
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Date deposited: 19 Nov 2020 17:31
Last modified: 17 Mar 2024 06:04
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Contributors
Author:
Doraid Dalalah
Author:
Udechukwu Ojiako
Author:
Maxwell Chipulu
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