Inventory Management, Metrics, and Simulation.

MARTIN, BENJAMIN ROBERT. Inventory Management, Metrics, and Simulation. (Under the direction of Jeffrey A. Joines and Kristin A. Thoney-Barletta). Today’s competitive markets challenge companies and their supply chains to balance speed, flexibility, quality, and responsiveness with low cost. To address these challenges, the area of supply chain management has become vital to the success of a company as supply strategies are set. Performance measures are critical for the successful implementation and assessment of a supply chain strategy. As organizations implement Lean and other continuous improvement strategies to meet the needs of today’s marketplace, traditional financial measures and performance measurement frameworks fail to properly gauge the benefits. This paper presents an overview of the predominant performance measurement frameworks in the literature and a proposed framework for Lean supply chains. Metrics from the supply chain literature are categorized using the proposed framework. The preponderance of the paper discusses a supply chain inventory management problem in industry. Companies are faced with global competition and, in an effort to retain market share, are attempting to lower finished goods inventory while maintaining or increasing customer service levels. This paper discusses the application of a novel technique for integrating ideality with the system operator to a real world supply chain inventory management problem. The system operator and ideality are TRIZ tools that allow one to develop an understanding of a problem as well as lead to novel solution generation. Integrating the two tools may provide new insights into the problem at hand. Ideality and the system operator are briefly summarized along with the methodology for integrating the two tools. An inventory model was developed to address the problem. A simulation study using actual demand, finished goods inventory, and forecasts was conducted to evaluate the average inventory and fill rates of different proposed inventory policies. The best policy from the simulation study set inventory targets at the SKU level while taking into account forecast inaccuracies. A pilot implementation of this inventory policy was successful and the apparel company implemented the model. The model that was implemented ignored variability with regards to the lead-time. The lead-time variability inherent in the system was causing poor fill rates. Therefore, the inventory model was extended to incorporate lead-time variability. Using a simulation study, the new proposed inventory model was evaluated and compared to six inventory models from the literature. The inventory models are compared using cycle service, average fill rate, and average inventory. The study considers a range of demand and lead-time scenarios using both theoretical and actual data. The proposed inventory model is shown to perform comparable to models from the literature but is easier to understand by the apparel company’s senior management. Inventory Management, Metrics, and Simulation by Benjamin Robert Martin A dissertation submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Textile Technology Management Raleigh, North Carolina 2010