Throughput of multiple-deep AS/RS for heterogeneous paper reels depending on the number of stock keeping units, average filling levels, and order reorganization

Abstract Automated block storage systems are characterized by a high degree of space utilization. This paper focus on a system with automatically operating overhead cranes in multiple-deep storage and retrieval systems for paper reels. They have gained in importance due to the steadily growing demand for packaging paper in recent years. The warehouses based on them act as a buffer to decouple the paper machines, which produce around the clock, from the shipping process, which usually only runs for up to 16 hours a day, five days a week. It is of high importance for investors and operators to know the performance of such a warehouse under different operating conditions. Multiple-deep storage systems are characterized by the fact that there is direct access only to the uppermost loading unit in a stack. If a paper reel needs to be retrieved from a lower position within a stack, time-consuming relocations are necessary. Therefore, the current inventory or the storages average filling level (AFL), the number of stock keeping units (NoSKU), and the existing number of mixed stacks are interesting factors. In addition, the effects of order reorganization (OR) are to be investigated if the retrieval orders are already known several hours in advance. During periods of low crane utilization, the warehouse management system (WMS) can instruct to build stacks of reels required for an order on top of each other, so that fewer or no relocations are required when orders are called off. Based on theoretical principles for ideal space utilization, framework conditions for realistic modeling of such systems with heterogeneous loading units of different dimensions are presented in this article. For the first time, strategies and a new algorithm in WMS for them are described in detail. For an exemplary warehouse with realistic conditions such as a constant daily production volume and fluctuating shipment quantities, the case study in this article shows the effects of the factors mentioned and a newly introduced factor on system performance.