Abstract

Inventory is an important part of supply chain management as it directly impacts both cost and service. As demand is more or less uncertain and it takes time to manufacture and deliver the goods, some amount of inventory is required somewhere in the chain to provide the required service to the end customer. Increasing supply chain inventories increases customer service and consequently revenue, but it comes at a higher cost. The aim of supply chain inventory management is to optimize the inventories and to shift the current customer service curve outward through improved inventory strategies and redesigning the supply chain. This thesis is aimed at studying the effectiveness of various factors in the supply chain environment with and without postponement strategies. Analysis of these factors enables a better understanding of the supply chains and will help to design these systems more effectively. Simulation models are developed using Arena and are used to capture the system dynamics with probability distribution which provides valuable insight into which variables are the most important and how variables interact. It also helps to capture the uncertainty and stochastic nature of the model. Two-level Fractional Factorial Experimental designs are used to study and analyze the performance of service level and inventory levels and to determine which variables are the most influential.