Nowadays firms must develop inventory policies that enable them to cope with the changing marketplace. Determining proper inventory locations can help decrease costs related to inventory holding and transportation. Moreover, this allows firms to respond in a timely manner to customers’ requirements. As a result profit margins can be enhanced as well as the competitiveness of a firm. However, the decision of where to locate inventory in a supply chain is difficult since many companies are managed independently. The present research is developed as a case study where product classification, customer and supplier segmentation schemes are reviewed in order to determine appropriate inventory locations along the supply chain. The thesis is written upon literature and empirical research, where most of the data was collected through personal interviews and observations at the supply chain management offices of a distributor for sealing material parts in Europe. Our conclusion shows that product classification has an important impact on inventory location decisions. Also, we conclude that products should be classified based on both physical characteristics and demand factors, as well as according to customers’ requirements. Another factor to be considered when deciding on inventory location is supply risks, due to issues related to raw material availability and capacity. Nonetheless, the selection of classification variables is challenging as it is hard to determine which factors are more relevant than others as this varies depending on each firms’ needs. In addition, we find that supply chain strategies are not realistic due to the constant changes in the business environment and the inability of a firm to manage whole supply chains. Furthermore, a high level of communication among supply chain partners is fundamental, especially when a centralized inventory policy and a postponement strategy are in place.

We consider a single-part, two-echelon supply chain problem for spare parts. The network consists of a single manufacturing plant, a set of service centers (SCs) and a set of customers. Both echelons keep spare parts using the base-stock replenishment policy. The plant behaves as an M/M/1 queueing system and has limited production and storage capacity. Demand faced by each SC follows an independent Poisson process. The problem is to determine optimal location-allocation and optimal base-stock levels at both echelons while satisfying the target service levels and customer preferences of SCs. We develop a mixed integer non-linear programming model and use cutting-plane method to optimize the inventory-location decisions. We present an exact solution procedure for the inventory stocking problem and demonstrate the limitations of using traditional inventory models like METRIC-like and Approximate in case of high utilization rates. We show the effectiveness of our proposed cutting-plane algorithm and provide important managerial insights for spare parts management.

We consider a single-part, two-echelon supply chain problem for spare parts. The network consists of a single manufacturing plant, a set of service centers (SCs) and a set of customers. Both echelons keep spare parts using the base-stock replenishment policy. The plant behaves as an M/M/1 queueing system and has limited production and storage capacity. Demand faced by each SC follows an independent Poisson process. The problem is to determine optimal location-allocation and optimal base-stock levels at both echelons while satisfying the target service levels and customer preferences of SCs. We develop a mixed integer non-linear programming model and use cutting-plane method to optimize the inventory-location decisions. We present an exact solution procedure for the inventory stocking problem and demonstrate the limitations of using traditional inventory models like METRIC-like and Approximate in case of high utilization rates. We show the effectiveness of our proposed cutting-plane algorithm and provide important managerial insights for spare parts management.