Abstract
A push–pull supply chain is a hybrid of “push” and “pull” supply chains where semi-finished products are produced by forecasts and “pushed” to a stock point, then are “pulled” by actual customer orders and go through remaining processes to be delivered. In order to design an effective push–pull supply chain, there are two critical issues in the decision making process: how to support decision makers to identify feasible locations for demand fulfillment points based on the product, process, and organizational form of a given enterprise, and how to support decision makers to improve the customer lead time management capability of a push–pull supply chain. In this study, we present a decision support system for designing a push–pull supply chain that 1) incorporates the product, process, and organizational form of a given enterprise; 2) leverages a new hybrid push–pull control model, which enhances the customer lead time management capability; and 3) provides a decision support model that supports decision makers for performing scenario-based analysis in designing a push–pull supply chain. The numerical analysis exhibits how the proposed system can be implemented in the context of a semiconductor supply chain, and subsequently shows that our control model results in substantial improvement of customer lead time management capability over conventional push–pull supply chain designs without a significant inventory cost increase. Also, some experimental results are provided to support decision makers on how to make the transition from the conventional design to the proposed one.
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