TITLE:
Optimization of Operations by Simulation—A Case Study at the Red Cross Flanders
AUTHORS:
Karen Moons, Helena Berglund, Valerie De Langhe, Katrien Kimpe, Liliane Pintelon, Geert Waeyenbergh
KEYWORDS:
Optimization, Simulation, Operations Flow, Blood Supply Chain
JOURNAL NAME:
American Journal of Industrial and Business Management,
Vol.6 No.10,
October
19,
2016
ABSTRACT: The Blood
Service at the Belgian Red Cross-Flanders is responsible for blood collection
in Flanders (Belgium). One of their missions is guaranteeing a constant and
sufficient supply of safe blood products. This is a critical public health
need, since the blood products can save lives of victims from traffic accidents
or in the event of major blood losses in hospitalized patients. The main
objective of this project is optimizing the operations flow in donor centers,
in such a way that the waiting time for donors is minimized and that the donor
center occupation or productivity is maximized. In this case study, the flow of
three types of donations is investigated. Blood and plasma are donated in all
donor centers (i.e. 11 donor centers in Flanders), while
blood platelets are collected in only six donor centers. Based on data
collected from the 11 donor centers in Flanders, a simplified simulation model
was developed, which can be used to optimize the operations flow based on the
expected number of donors and their moment of arrival at the donor center. The
simulation model is built in Enterprise Dynamics 9.0 simulation software. The
input data in the model are data that have been collected in collaboration with
the Belgian Red Cross-Flanders. Different scenarios will be analyzed to gain
insight in the impact of small changes in the input parameters on the
performance of the flow. In this paper, a gap analysis is conducted to identify
extra data needs. With these additional data, a more detailed model can be
constructed to test the scenarios, and a dynamic planning tool will be
developed to rely on when setting up the capacity of the donor center in order
to find a scenario with the most optimized flow.