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Manufacturing managers face increasing pressure to reduce inventories across the supply chain. However, in complex supply chains, it is not always obvious where to hold safety stock to minimize inventory costs and provide a high level of service to the final customer. In this paper we develop a framework for modeling strategic safety stock in a supply chain that is subject to demand or forecast uncertainty. Key assumptions are that we can model the supply chain as a network, that each stage in the supply chain operates with a periodic-review base-stock policy, that demand is bounded, and that there is a guaranteed service time between every stage and its customers. We develop an optimization algorithm for the placement of strategic safety stock for supply chains that can be modeled as spanning trees. Our assumptions allow us to capture the stochastic nature of the problem and formulate it as a deterministic optimization. As a partial validation of the model, we describe its successful application by product flw teams at Eastman Kodak. We discuss how these flow teams have used the model to reduce finished goods inventory, target cycle time reduction efforts, and determine component inventories. We conclude with a list of needs to enhance the utility of the model.
(Base-Stock Policy; Dynamic Programming Application; Multi-echelon Inventory System; Multi-Stage Supply-Chain Application; Safety Stock Optimization)
1. Introduction
Manufacturing firms are subject to pressure to do everything faster, cheaper, and better. Firms are expected to continue to improve customer service by increasing on-time deliveries and reducing delivery lead-times. At the same time, they must provide this service more cheaply and utilize fewer assets. Increasingly, firms need to do this for a global marketplace.
This pressure to improve forces companies to look at their operations from a supply-chain perspective and to seek improvements from better coordination and communication across the supply chain. A supply-chain perspective is essential to avoid some of the local suboptimization that occurs when each step in a process operates independently with its own metrics and rewards. Using a supply chain as a focusing mechanism challenges an organization to examine cross-functional solutions to address some of the barriers that inhibit improvements.
The primary intent of this research is to develop a tactical tool to help...