OPTIMIZATION OF WAREHOUSE INVENTORY SPACE USING CLASS BASED STORAGE METHOD

Abstract

Warehouse inventory management is a crucial aspect of supply chain management. Efficient warehouse inventory management not only ensures smooth operations but also contributes to cost savings. One of the critical challenges that warehouse manager’s face is optimizing inventory space. With limited space available, warehouse managers need to ensure that the inventory is well-organized and utilized optimally. The Fast, Slow, and Non-moving (FSN) analysis technique has emerged as an effective tool to optimize warehouse inventory space. The FSN analysis technique categorizes inventory items based on their demand patterns. Fast moving items are those that have a high turnover rate, while slow-moving items have a lower turnover rate. Non-moving items are those that have not been sold or used for an extended period. By analyzing the demand patterns of different inventory items, the FSN analysis technique helps warehouse managers identify slow-moving and non-moving items that can be either discarded or moved to a different location to free up warehouse space. This project work presents a detailed analysis of the application of the FSN analysis technique to optimize warehouse inventory space. The study involved collecting inventory data from a warehouse and categorizing the inventory items using the FSN analysis technique. The analysis revealed that slow-moving and non-moving items occupied a significant amount of warehouse space. Based on this analysis, the study recommended various strategies to optimize warehouse inventory space, such as increasing the frequency of stocktaking, reducing the order quantity of slow-moving items, and transferring non-moving items to an offsite location. The study found that implementing these strategies significantly improved warehouse inventory management, resulting in increased space utilization and cost savings. The study found that the FSN analysis technique helped warehouse managers to identify 20% of items that were slow-moving or non-moving, occupying 40% of the warehouse space. Overall, this study suggests that the FSN analysis technique is a powerful v tool for warehouse managers seeking to optimize inventory space and improve warehouse efficiency. By categorizing inventory items based on their demand patterns, warehouse managers can identify slow-moving and non-moving items and implement strategies to optimize space utilization.