Publication Date
Authored by
Dong Guo
Topic(s) Covered:
  • Manufacturing
  • Inventory

Inventory planning is one of the most important processes in supply chain management that plays an important role in the success of an Engineer-to-Order (ETO) business. Supply chain and inventory managers in ETO businesses always face challenges in determining an appropriate inventory level because of the uncertainty nature of the ETO industry. In particular, for the steel ETO industry, better inventory planning will help the company reduces the inventory cost significantly. This capstone studies the raw materials inventory planning of an ETO utility infrastructure manufacturer. The current inventory planning of the sponsor company is outdated and does not meet the required service level. Thus, the company aims to improve its inventory management system by replacing the traditional methods with scientific- based ones. In the initial stage of this capstone, several challenges such as uncertain demand, uncertain lead time, uncertain project bid win/loss possibility have been identified that affect the inventory decisions of the company. This capstone focuses on the normal business process, which does not consider unexpected demand surge, and which assumes winning the returning project. This study first identifies the models applicable to the company and then compares the total cost of the selected models under a centralized (aggregated) decision process. Two inventory planning models (s,Q model and R,S model) were studied. The main contribution of the model is to suggest optimal safety stock level, review period, and order quantity to the company. After comparing the total cost of the two models, the (R,S) model was chosen. This model will help the case company to optimize the inventory spending on an annual basis. Sensitivity analysis was conducted on lead time and service level (CSL) of the (R,S) model. Further studies are suggested to capture the unexpected demand surge, uncertain lead time, new project win/loss, etc.