Comparison of Alternative Configurations for Dense Warehousing Systems

In heavily constrained environments requiring very high density storage, traditional aisle-based warehousing may not provide viable options. One feasible manifestation of high density storage systems is the ‘puzzle-based’ system, in which unit loads are moved through the system via manipulation of empty (escort) locations to retrieve desired items. Another option would be the use of movable concentric rings, with escorts being utilized to enable lateral movements of unit loads between the rings. In this paper, the authors present analytical results to compare retrieval time performance for these two types of high density storage systems for randomly demanded items under various assumptions regarding the initial placement of escorts. The paper concludes that the use of movable concentric rings results in significant improvement to retrieval time performance in comparison to rectangular, puzzle-based systems, and further concludes that additional research is warranted

Modelling load retrievals in Puzzle-Based Storage systems

Puzzle-based storage systems are a new type of automated storage systems that allow storage of unit loads (e.g. cars, pallets, boxes) in a rack on a very small footprint with individual accessibility of all loads. They resemble the famous 15-sliding tile puzzle. Current models for such systems study retrieving loads one at a time. However, much time can be saved by considering multiple retrieval loads simultaneously. We develop an optimal method to do this for two loads and heuristics for three or more loads. Optimal retrieval paths are constructed for multiple load retrieval, which consists of moving multiple loads first to an intermediary ‘joining location’. We find that, compared to individual retrieval, optimal dual load retrieval saves on average 17% move time, and savings from the heuristic is almost the same. For three loads, savings are 23% on average. A limitation of our method is that it is valid only for systems with a very high space utilisation, i.e. only one empty locatio

Flexible high-density puzzle storage systems

In a traditional storage system, when one of the mechanical or electrical parts or the software fails to operate correctly, it may lead to the failure of the entire system imposing huge costs to the system (Gue et al., 2014). However, in a grid storage network, if a grid fails to operate, the system continues to operate. Therefore, failure of a system component will not jeopardize the whole system functionality. As such, reliability is one of the key advantages of grid storage networks. Another benefit of grid storage systems is flexibility. Various systems such as GridFlow, GridPick, GridStore, are developed that consist of multiple autonomous conveyors to store and move items in different directions. A unit module is capable to work independently. To retrieve an item, empty modules open a temporary aisle to move the item to the retrieval point. This study developed a tote retrieval algorithm for high-density storage systems (HDSS). The algorithm is capable of retrieving totes from all sides of a storage puzzle. This is novel since methodologies of prior studies were confined to retrieving items from a single grid or a single side of a puzzle. The algorithm was decentralized and agent-based where each grid acts as an agent. The study undertook developing algorithms that could minimize the number of movements in the network for tote retrievals and to prevent deadlocks. Deadlock prevention algorithms are capable to resolve a diverse range of situations that cause network deadlocks. An object-oriented software program was developed that implemented the algorithms. The software tool simulated puzzles of various sizes with different number of escorts available for retrieving requested totes. Thousands of iterations of the puzzle configurations were resolved for the analysis. It was found that incremental increase in the number of escorts in the puzzle reduces the number of movements for retrieving totes. However, depending on the puzzle size, there were increments that additional escorts had minimal impact. It was also found that average retrieval movements for 3 totes increase logarithmically with the number of cells in a puzzle. To validate the methodology and its software implementation, results from the simulation were compared with the results from other studies with mathematical solutions. The program replicated the optimum number of movements for a puzzle that contained one escort and retrieved one tote

Robotized Warehouse Systems: Developments and Research Opportunities

Robotized handling systems are increasingly applied in distribution centers. They require little space, provide flexibility in managing varying demand requirements, and are able to work 24/7. This makes them particularly fit for e-commerce operations. This paper reviews new categories of robotized handling systems, such as the shuttle-based storage and retrieval systems, shuttle-based compact storage systems, and robotic mobile fulfillment systems. For each system, we categorize the literature in three groups: system analysis, design optimization, and operations planning and control. Our focus is to identify the research issue and OR modeling methodology adopted to analyze the problem. We find that many new robotic systems and applications have hardly been studied in academic literature, despite their increasing use in practice. Due to unique system features (such as autonomous control, networked and dynamic operation), new models and methods are needed to address the design and operational control challenges for such systems, in particular, for the integration of subsystems. Integrated robotized warehouse systems will form the next category of warehouses. All vital warehouse design, planning and control logic such as methods to design layout, storage and order picking system selection, storage slotting, order batching, picker routing, and picker to order assignment will have to be revisited for new robotized warehouses

Advanced Storage and Retrieval Policies in Automated Warehouses

Warehouses are key components in supply chain. They facilitate the product flow from production to distribution. The performance of supply chains relies on the performance of warehouses and distribution centers. Being able to realize short order delivery lead times, in retail and ecommerce particularly, is important for warehouses. Efficient and responsive storage and retrieval operations can help in realizing a short order delivery lead time. Additionally, space scarcity has brought some companies to use high-density storage systems that increase space usage in the warehouse. In such storage systems, most of the available space is used for storing products, as little space is needed for transporting loads. However, the throughput capacity of high-density storage systems is typically low. New robotic and automated technologies help warehouses to increase their throughput and responsiveness. Warehouses adapting such technologies require customized storage and retrieval policies fit for automated operations. This thesis studies storage and retrieval policies in warehouses using several common and emerging automated technologies

A Decentralized Control Strategy for High Density Material Flow Systems with Automated Guided Vehicles

This work presents a universal decentralized control strategy for grid-based high-density material flow systems with automated guided vehicles and gives insights into the system behavior as well as the solution quality