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Project

The trade-off between inventories, lead time and capacity: application to vaccine supply chain design.

This doctoral dissertation contributes to the modeling and measuring of the operational performance of a vaccine manufacturing supply chain. These models are part of a broader, overarching framework on stakeholder-based vaccine supply chain design. We show how the developed models in this doctoral dissertation are positioned in that framework. The overarching framework consists of five steps to generate and evaluate new (vaccine) supply chain designs. According to this five-step framework we emphasize the involvement of relevant stakeholders to design a new vaccine supply chain. Such stakeholders are not limited to the people or parties involved with the vaccine manufacturing, but may also include NGOs, governments and WHO among others. All these stakeholders are interested in different aspects of a vaccine supply chain design and therefore we propose to classify a (vaccine) supply chain's performance measures into three distinct categories: economical, technological and value performance measures. Subsequently a diverse and balanced set of performance measures should be derived in such a way that it can be used to evaluate new supply chain designs. Finally, we propose a method to rank different vaccine supply chain designs and to choose a single supply chain design to be implemented.

We demonstrate the guaranteed service approach as an important building block to model a (vaccine) supply chain network. This particular approach is a pragmatic approach to minimize a supply chain network's safety stock. We illustrate this approach with a desktop example and we emphasize the difference between the guaranteed service approach with deterministic and variable lead times. For both approaches, a key assumption is that the lead times are independent of the capacity. This assumption is relaxed in the remainder of the thesis. We demonstrate how the lead times of a guaranteed service supply chain network's manufacturing stages can be modeled as a function of the production capacity. Therefore we rely on batch queuing networks. By the integration of these two well-established methodologies, we can verify the impact of the lead time determinants on the safety stock. We demonstrate our integrated methodology with a published dataset and finally we apply it to a vaccine supply chain. Finally, we elaborate on the quality-related processes of a vaccine supply chain. These processes are complex and face long and variable lead times. These long lead times are also a consequence of limited capacity (both people and equipment) and therefore we model these processes with queuing networks such that we are able to observe the impact of adding capacity at different stages in the supply chain network.

Date:1 Oct 2013 →  23 Oct 2018
Keywords:Supply Chain Design
Disciplines:Applied economics, Economic history, Macroeconomics and monetary economics, Microeconomics, Tourism
Project type:PhD project