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 Integrated Network Modeling Framework for Analysis of Multi-line Order Pick Systems

Due to demanding service levels in E-commerce order fulfillment, modeling and analysis of order picking processes in warehouses deserve special attention. With a particular focus on multi-line E-commerce orders, we develop modeling tools that are necessary to analyze the order consolidation delays in the downstream pick stations. We develop a queuing network modeling framework for integrated analysis of upstream (storage system) and downstream (pick system). We apply our modeling approach to an integrated order-pick system that includes a shuttle-based storage and retrieval system, and a single pick station. Using simulations, we test the effect of the storage system configuration on the order throughput time

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

Design and Control of Warehouse Order Picking: a literature review

Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for its warehouse, and consequently for the whole supply chain. In order to operate efficiently, the orderpicking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.Order picking;Logistics;Warehouse Management

A Review on Automated Storage/ Retrieval Systems and Shuttle Based Storage/Retrieval Systems

Automated storage and retrieval systems are warehousing systems that are used for the storage and retrieval of products in both distribution and production environments. Shuttle based storage/retrieval systems are composed of elevators with lifting tables that are attached on a mast, shuttle carriers, buffer positions and the storage racks. It is observed that the shuttle based storage/retrieval systems increases the throughput capacity of the systems compared to automated storage/retrieval systems. Shuttle based storage/retrieval systems is relatively a new technology in automated storage and retrieval systems and usually works with aisle and tier captive shuttles. This new technology is mostly used for mini-load warehouses. The main body of the paper consists of an overview of literature discussing automated storage/retrieval systems and shuttle based storage/retrieval systems

Order-picking workstations for automated warehouses

The FALCON (Flexible Automated Logistic CONcept) project aims at the development of a new generation of warehouses and distribution centers with a maximum degree of automation. As part of the FALCON project, this dissertation addresses the design and analysis of (automated) workstations in warehouses with an end-of-aisle order-picking system (OPS). Methods are proposed for architecting, quantifying performance, and controlling such a system. Four main topics are discussed in this dissertation. First, a modular architecture for an end-of-aisle OPS with remotely located workstations is presented. This architecture is structured into areas and operational layers. A hierarchical decentralized control structure is applied. A case of an industrial-scale distribution center is presented to demonstrate the applicability of the proposed architecture for performance analysis using the process algebra-based simulation language $\chi$ (Chi). Additionally, it is demonstrated how the architecture allows straightforward modification of the systems configurations, design parameters, and control heuristics. Second, a method to quantify the operational performance of order-picking workstations has been developed. The method is based on an aggregate modeling representation of the workstation using the EPT (Effective Process Time) concept. A workstation is considered in which a human picker is present to process one customer order at a time while products for multiple orders arrive simultaneously at the workstation. The EPT parameters are calculated from arrival and departure times of products using a sample path equation. Two model variants have been developed, namely for workstations with FCFS (First-Come-First-Serve) and for workstations with non-FCFS processing of products and orders. Both models have been validated using data from a real, operating workstation. The results show that the proposed aggregate modeling methodology gives good accuracy in predicting product and order flow time distributions. Third, the dissertation studies the design and control of an automated, remotely located order-picking workstation that is capable of processing multiple orders simultaneously. Products for multiple orders typically arrive out-of-sequence at the workstation as they are retrieved from dispersed locations in the storage area. The design problem concerns the structuring of product/order buffer lanes and the development of a mechanism that overcomes out-of-sequence arrivals of products. The control problem concerns the picking sequence at the workstation, as throughput deteriorates when a poor picking sequence is applied. An efficient control policy has been developed. Its performance is compared to a number of other picking policies including nearest-to-the-head, nearest neighbor, and dynamic programming. Subsequently, the resulting throughput and queue length distribution are evaluated under different settings. Insights for design considerations of such a system are summarized. Finally, the dissertation reflects on the findings from the proposed methods and uses them to come up with comprehensive design principles of end-of-aisle OPS with remotely located workstations. The various issues influencing the performance of such a system are highlighted. Moreover, the contribution of each proposed method with regards to these issues is delineated

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

Modeling, Analysis, and Design Insights for Shuttle-based Compact Storage Systems

Shuttle-based compact systems are new automated multi-deep unit-load storage systems with lifts that promise both low operational cost and large volume flexibility. In this paper, we develop novel queuing network models to estimate the performance of both single-tier and multi-tier shuttle-based compact systems. Each tier is modeled as a multi-class semi- open queuing network, whereas the vertical transfer is modeled using an open queue. For a multi-tier system, the models corresponding to tiers and vertical transfer are linked together using the first and second moment information of the queue departure processes. The models can handle both specialized and generic shuttles, and both continuous and discrete lifts. The accuracy of the models is validated through both simulation and a real case. Errors are acceptable for conceptualizing initial designs. Numerical studies provide new design insights. Results show that the best way to minimize expected throughput time in single-tier systems is to have a depth/width ratio around 1.25. Moreover, specialized shuttles are recommended for multi-tier systems because the higher cost of generic shuttles is not balanced by savings in reduced throughput time and equipment need

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

A survey of literature on shuttle based storage and retrieval systems

Prethodna decenija donela je pravi procvat u oblasti automatskih skladišnih sistema (SBS/RS) baziranih na šatl tehnologiji u mnogim industrijama. Njihova superiornost u odnosu na 'mini-load' automatske skladišne sisteme ogleda se prvenstveno u mogućnosti većeg protoka skladišnih jedinica kroz sistem, velikoj fleksibilnosti proširenja sistema i mnogo boljoj energetskoj efikasnosti, koja je rezultat manje potrošnje energije i sposobnosti regeneracije velike količine energije. Sveobuhvatan pregled literature SBS/RS prikazan u ovom radu ukazuje na glavne specifičnosti, ključne pretpostavke i aproksimacije u razvijenim modelima za procenu vrednosti performansi sistema ili strategijama za upravljanje sistemom, i ističe najvažnije zaključke izvedene iz dobijenih rezultata. Predstavljeni pristupi u modeliranju sistema mogu biti koristan alat za projektante SBS/RS prilikom procene efikasnosti sistema u početnoj fazi projektovanja.The last decade brought the blooming of the shuttle-based automated storage and retrieval system (SBS/RS) in many industrial applications. They proved the superiority over the mini-load automated storage and retrieval system mainly due to higher throughput capacity, high flexibility of future extension, much better energy efficiency resulting from lower energy consumption and high energy regeneration capability. A comprehensive literature review on SBS/RS given in the paper pointed out main specifics and crucial approximations and assumptions of the developed system performance estimation models or control strategies, as well as the main conclusions resulting from the obtained results. Presented modeling approaches could be a valuable tool for SBS/RS designers and other related decision makers to estimate the system efficiency in the starting phase of SBS/RS design activities