The impact of COI-based storage on order-picking times

Background: The increasing competitiveness on the global markets enforces the need for a fast and reliable delivery. This task is possible to perform by improving the order-picking systems. The implementation of automated storage and retrieval systems (AS/RS) is not always profitable. In the warehouses where the order-picking is performed in accordance with the principle of picker-to-part rule, the picking efficiency optimization includes among others: the warehouse layout, the storage policy, the routing heuristic, the way of zoning, the order-batching method, and the sequencing of pick-lists. In the paper the impact of the storage policy on the order-picking times is checked. Methods: The influence of storage based on Heskett’s cube-per-order index (COI) on the average order-picking times is analyzed. The items based on increasing values of COI index are divided on classes. To determine the demand for items the analytical function proposed by Caron is used. Results: In the paper the benefits of storage based on COI index are compared with random storage and storage based only on picking frequency. It is assumed that the bin, to which the picker collects items has limited capacity – some orders has to be divided on smaller pick-lists. The analysis was performed using simulation tools. Additionally, the algorithm (taking into account different sizes of picker’s bin) for order-batching is presented. Conclusions: The analysis shows that the COI-based storage is particularly effective when the size of items increases. The COI-based curve is less skewed than the curve based only on picking frequency. The choice of storage policy should be carried out together with routing heuristic. The use of batching algorithm significantly increases the effectiveness of the order-picking process, but the optimal size of picker’s bin (and batch) should be optimized with consideration the sorting process.