A Decision support system for inventory management of information technology spare parts

Rising operational costs have become a major issue in developing countries, causing many leading information technology (IT) companies to focus on inventory optimization. This thesis research concentrates on inventory policy optimization and decision making process. We develop a decision support system (DSS) that provides an optimal control of IT spare part inventory to minimize the total cost. The system supports a continuous review (Q, r) inventory policy and a periodic review (S, s) inventory policy options for managing the spare parts inventory. The DSS includes a forecast model to estimate the failure rates of different device types purchased in different time periods. It is also enhanced by a simulation environment which evaluates different inventory management scenarios and choses the optimum one. Next, the DSS is applied to a real system and optimum inventory management scenario is determined according to the cost and service performances. Experimental design analysis is performed to measure the sensitivity of optimal total cost with respect to input parameters such as inventory holding cost, part order cost and penalties. The DSS provides an efficient, effective and flexible decision making environment for the optimal control of IT spare parts.