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Inventory Models Motivated by Biopharmaceutical Manufacturing

  • Author(s): Wang, Yang
  • Advisor(s): Kaminsky, Philip
  • et al.
Abstract

The biopharmaceutical industry now is entering a more mature stage of its existence. In order to prepare for increasingly fierce competition, firms are beginning to shift their focus from developing new technology to improving manufacturing operations. However, the nature of biomanufacturing poses many unique challenges for the industry. In this thesis, we consider three closely related inventory models to address the challenges these firms are facing.

In the first model, we consider an inventory planning model with batch differentiation. Batch production is a natural constraint in biomanufacturing and the decision of how many batches to produce and how to differentiate the batches is crucial. In this work, we propose a series of heuristic algorithms using the idea of certainty equivalent control which converts a difficult stochastic integer programing to a deterministic problem. We show that our heuristic algorithms perform extremely well when the demand variation is small and we also explore how the trade-off between demand information and decision dynamics affects the performance.

In the second model we combine the inventory model with a queuing model to address the tactical level supply chain management and coordination issue between the manufacturer and a third party contractor. Small biopharma firms usually outsource the filling/labeling/packing operations to a third party contractor. As a consequence, the firm experiences large uncertainty in the time until the outsourced order is returned. We show that a capacity reservation contract that places an order at fixed intervals with a capacity constraint can outperform the traditional inventory management $(r,q)$ policy by not only reducing the inventory cost at the firm, but also increasing the total profit of the entire system.

In the third model, we extend the traditional process flexibility literature by integrating inventory capabilities and give general guidelines on how to design an effective supply chain network. Given the expensive inventory storage capability in the biopharmaceutical industry, firms are often interested in incorporating flexible plants that can produce multiple types of product into an existing dedicated supply chain to better respond to demand uncertainty. We develop models that help the firm explore many important strategic issues, such as whether a new plant should be flexible or not, and whether and which plants should be modified to have inventory capabilities.

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