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

An approach for computing AS/R systems travel times in a class-based storage configuration

This study provides an approach to compute the travel time for AS/R systems in a class-based storage environment. A regression analysis is completed in order to define the importance of the key predictors taken into account and to propose a formulation of travel times. The results show the reliability of the model and allow to evaluate the travel time through the identification of a complete list of predictors. The proposed approach supports managers in theex-ante definition of travel times for a warehouse. A correct evaluation of travel times enables a better monitoring of the performance of warehouse operations and can support practitioners in the choice of the configuration not only in terms of kind of cycle, but also from a policy assignment perspective. From a theoretical point of view, this work can be considered as an attempt to refine the existing methods to compute travel times

On the Determinations of Class-Based Storage Assignments in AS/RS having two I/O Locations

This paper presents the use and extension of a geometrical-based algorithmic approach for determining the expected S/R machine cycle times, and therefore warehouse throughput, for class-based storage assignment layouts in an AS/RS.The approach was designed for the purpose of solving a practical storage assignment design problem for a major European manufacturer.The algorithm may be used to layout racks that are either "square-in-time (SIT)" or "non-square in time (NSIT)" with single or multiple I/O points.It is believed that use of this approach can result in the expedient evaluation of warehouse throughput resulting from new layouts, or re-layouts, of AS/R system racks, thus making these systems more appealing for use in integrated supply chain systems in general.production management;manufacturing;supply chain mangement;warehousing;storage

A reinforcement learning approach for transaction scheduling in a shuttle-based storage and retrieval system

With recent Industry 4.0 developments, companies tend to automate their industries. Warehousing companies also take part in this trend. A shuttle-based storage and retrieval system (SBS/RS) is an automated storage and retrieval system technology experiencing recent drastic market growth. This technology is mostly utilized in large distribution centers processing mini-loads. With the recent increase in e-commerce practices, fast delivery requirements with low volume orders have increased. SBS/RS provides ultrahigh-speed load handling due to having an excess amount of shuttles in the system. However, not only the physical design of an automated warehousing technology but also the design of operational system policies would help with fast handling targets. In this work, in an effort to increase the performance of an SBS/RS, we apply a machine learning (ML) (i.e., Q-learning) approach on a newly proposed tier-to-tier SBS/RS design, redesigned from a traditional tier-captive SBS/RS. The novelty of this paper is twofold: First, we propose a novel SBS/RS design where shuttles can travel between tiers in the system; second, due to the complexity of operation of shuttles in that newly proposed design, we implement an ML-based algorithm for transaction selection in that system. The ML-based solution is compared with traditional scheduling approaches: first-in-first-out and shortest process time (i.e., travel) scheduling rules. The results indicate that in most cases, the Q-learning approach performs better than the two static scheduling approaches

An approach for computing AS/R systems travel times in a class-based storage configuration

This study provides an approach to compute the travel time for AS/R systems in a class-based storage environment. A regression analysis is completed in order to define the importance of the key predictors taken into account and to propose a formulation of travel times. The results show the reliability of the model and allow to evaluate the travel time through the identification of a complete list of predictors. The proposed approach supports managers in theex-ante definition of travel times for a warehouse. A correct evaluation of travel times enables a better monitoring of the performance of warehouse operations and can support practitioners in the choice of the configuration not only in terms of kind of cycle, but also from a policy assignment perspective. From a theoretical point of view, this work can be considered as an attempt to refine the existing methods to compute travel times

Dynamic Modelling of an Automated Vehicle Storage and Retrieval System and a Simulation Analysis of its Efficiency

In this paper operating-time models for single and multiple instructions are set up considering an AVS/RS (automated vehicle storage and retrieval system). The operation times of AVS/RS and AS/RS (automated storage and retrieval system) are simulated in different situations by changing the shelf structure and order density. The results show that the AVS/RS is more efficient than the AS/RS in all situations. Furthermore, the numbers of rows and columns of storage shelves greatly influence the operation time. The graph of operation-time compression ratio against number of columns shows an inverted U-type distribution, and the compression ratio decreases and ultimately tends to zero as the number of rows is increased. Also, the order density affects the efficiency difference between the two systems: the higher the order density, the higher the AVS/RS operating-time compression rate. Finally, compared with the AS/RS, the AVS/RS operating-time compression ratio improves greatly with increasing density and number of rows because of parallel operations, whereas with decreasing density and number of rows the AVS/RS advantages are gradually lost and the compression ratio decreases and eventually even reaches zero

Progress in Material Handling Research: 2016

Table of contents

Automated Warehouse Systems: A Guideline for Future Research

This study aims to provide a comprehensive tool for the selection, design, and operation of automated warehouse systems considering multiple automated storage and retrieval system (AS/RS) options as well as different constraints and requirements from various business scenarios. We first model the retrieval task scheduling problem in crane-based 3D AS/RS with shuttle-based depth movement mechanisms. We prove the problem is NP-hard and find an optimality condition to facilitate the development of an efficient heuristic. The heuristic demonstrates an advantage in terms of solving time and solution quality over the genetic algorithms and the other two algorithms taken from literature. Numerical experiments illustrate that when a company tends to have multiple short planning horizons with small task batches (i.e., aims to increase the responsiveness level), adding more shuttles is helpful. However, if a company has a long planning horizon with a large task batch size, having faster cranes is more efficient to reduce the makespan. We then focus on the impacts of the number of shuttles, operational mode, storage policies, and shuttle dispatching rules on the expected cycle time of a tier-to-tier shuttle-based storage and retrieval system. The system is modeled as a discrete-time Markov Chain to derive the shuttle distribution under each scenario create the expected travel time models. Numerical experiments indicate that class-based storage is always better than the random storage policy. The best shuttle dispatching rule under each combination of the number of shuttles, operational mode, and storage policy can be quickly identified through the expected cycle time models which are simple and computation friendly. At last, we study the warehouse design problem considering the choice, design, and operation of 2D AS/RS and 3D AS/RS in a systematic way. The warehouse design problem under consideration aims to reduce the investment while satisfying different business needs measured by the desired throughput capacity. We propose a branch-and-bound algorithm to conquer the computational challenges. With the developed algorithm, an optimal warehouse design can be obtained under different application environments, characterized by the desired throughput capacity, inventory level, and demand rate of each SKU

Warehouse design and control: framework and literature review

In this paper we present a reference framework and a classification of warehouse design and control problems. Based on this framework, we review the existing literature on warehousing systems and indicate important gaps. In particular, we emphasize the need for design oriented studies, as opposed to the strong analysis oriented research on isolated subproblems that seems to be dominant in the current literature

Optimal Storage Rack Design for a 3-dimensional Compact AS/RS

In this paper, we consider a newly-designed compact three-dimensional automated storage and retrieval system (AS/RS). The system consists of an automated crane taking care of movements in the horizontal and vertical direction. A gravity conveying mechanism takes care of the depth movement. Our research objective is to analyze the system performance and optimally dimension of the system. We estimate the crane’s expected travel time for single-command cycles. From the expected travel time, we calculate the optimal ratio between three dimensions that minimizes the travel time for a random storage strategy. In addition, we derive an approximate closed-form travel time expression for dual command cycles. Finally, we illustrate the findings of the study by a practical example.AS/RS;Warehousing;Order Picking;Travel Time Model;Compact Storage Rack Design