Product availability improvement for analytical column supply chain : inventory optimization and lot sizing

Abstract

This thesis demonstrates the potential of a structured safety stock policy, and an improved lot sizing production policy on the inventory level and service level. The thesis focuses on incorporating demand variability into the factors of determining the safety stock level, and establishing a structured ordering and validation process. The thesis also incorporates setup cost and product nature into creating a new production policy that aims to significantly increase the service level for products in the Build to Order category. A detailed study and interview of the Waters Column Supply Chain are performed at the start of the project leading to a focus on service level and the objective of cost reduction. It has been determined that many challenges in the supply chain have arisen due to complexity and over execution of company aims of high product availability for Super A products. The thesis addresses the first challenge with a safety stock policy in which the safety stock is a function of the safety factor, lead time, and weekly standard deviation of the demand. This policy is later validated with a simulation based upon demand data and ordering pattern. For the new production policy, the author suggests an increase in production for Build to Order, while applying the Economic Order Quantity model. To validate the new policy and its effect, a simulation using the historical demand data is used to simulate the new cost and service level. From the simulation the author found a 99.5% service level and a 17% reduction in safety stock. At the same time the author introduces a new safety stock policy that is expected to mediate some of the challenges observed from the interviews. The simulation of the new production policy predicts a 17.3% increase in service level and a $6,606 reduction in cost.