## 4 Case Study  
This study focuses on the Wi-Fi modules produced by company H. The main components are stored on the heavy-duty shelves of the warehouse. The as-is model of the warehouse planning for Company H is to divide the space into multiple areas on the basis of the classifications of components under the assumption of sufficient storage space. However, in terms of the implementation of warehouse management, Company H faces some problems. Firstly, the prearranged storage spaces are sometimes not sufficient for receiving components; this rendered no fixed storage locations available. Moreover, because no fixed storage location is available for the components, no detailed storage location planning and arrangement system is used in company H's warehouse. Thus, the storage locations might not have been able to accommodate the receiving quantities of components, resulting in an incapacity to fix the shelf positions for components and subsequently forcing the on-site pickers to compare and search for components one by one, which in turn led to increased labor and time costs. Furthermore, when the system assigned an individual picker to one or more picking lists, it did not consider the storage locations of the components in the warehouse and the total load that pickers are capable of carrying. Consequently, the distance between the locations of the components assigned to a picker could have been far away, or the picking list could have exceeded the picker's maximum load, requiring multiple trips of picking to complete the picking work. This research collected 98 customer orders of Wi-Fi modules for company H. Based on these customer orders, manufacturing orders were generated and expanded in accordance with the BOM to obtain the required quantities of the lowest-level components. The storage space demand is planned on the basis of the number of components used. In addition, rolling storage location planning is performed on a 7-day cycle; that is, the quantities of components that would be purchased in the following week are reviewed every 7 days to dynamically adjust the storage space. The proportions of different component classifications relative to the quantities used were calculated to evaluate the storage space for each classification of components. After the component space demand was determined, the average DoS value of each component classification in the warehouse was calculated to decide the optimal storage locations for different component classifications as shown in Table 1. Each classification of components was arranged in the optimal storage location relative to the exit on the basis of the average DoS value as shown in Figure 2. Then, detailed storage location planning was performed for the same classifications of components. The first-in-first-out method was used to calculate the average DoS values of different components in the same classification. This research uses the integrated circuit (IC) components as an example to explain how to perform the detailed storage location planning. Table 2 shows the average DoS values of 39 IC components in the warehouse. Based on the storage space demands and the average DoS values of various types of IC components, the optimal detail storage location planning can be obtained as shown in Figure 3. Figure 3 presents the perspective of a picker facing the shelves where they stock and pick up IC components and the schematic diagram of the storage locations of the 39 IC components in area no. 5-AC. Shelf 15 is the location closest to the exit. Because the height of the shelf affects the convenience of picking, the components with the shortest DoS are arranged on the first shelf, which pickers can access without an elevator. The IC Components with long DoS values are arranged on the second and third shelves, which require an elevator for the pickers to reach. According to the above-mentioned principles, the optimal detail storage locations for all IC components are decided.