2,051 research outputs found

    Robotized Warehouse Systems: Developments and Research Opportunities

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    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

    Performance evaluation of shuttle-based storage and retrieval systems using discrete-time queueing network models

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    Shuttle-based storage and retrieval systems (SBS/RSs) are an important part of todayā€˜s warehouses. In this work, a new approach is developed that can be applied to model different configurations of SBS/RSs. The approach is based on the modeling of SBS/RSs as discrete-time open queueing networks and yields the complete probability distributions of the performance measures

    A survey of literature on shuttle based storage and retrieval systems

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    Prethodna decenija donela je pravi procvat u oblasti automatskih skladiÅ”nih sistema (SBS/RS) baziranih na Å”atl tehnologiji u mnogim industrijama. Njihova superiornost u odnosu na 'mini-load' automatske skladiÅ”ne sisteme ogleda se prvenstveno u mogućnosti većeg protoka skladiÅ”nih jedinica kroz sistem, velikoj fleksibilnosti proÅ”irenja sistema i mnogo boljoj energetskoj efikasnosti, koja je rezultat manje potroÅ”nje 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

    A Performance Calculator for Shuttle-based Storage and Retrieval System Design

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    In this study, we present an analytical model based tool that can estimate critical performance measures from a pre-defined shuttle-based storage and retrieval system (SBS/RS) design. SBS/RS is relatively a new automated storage and retrieval technology and mostly used for mini-load material handling. In this study, we develop an open queuing network model based tool estimating critical performance measures: the mean travel time of lifts/shuttles, utilization of lifts/shuttles, amount of energy consumption and energy regeneration per transaction, waiting times and number of jobs waiting in queues, etc., from a pre-defined SBS/RS design. By the developed tool, one can evaluate an SBS/RS designā€™s performance promptly by changing the input design parameters (e.g., distance between two adjacent bays/tiers, velocity of vehicles, acceleration/deceleration of vehicles, number of tiers, number of bays, number of aisles, arrival rates, weight of totes, etc.) in these systems

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

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    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

    Warehouse design and control: framework and literature review

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    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

    Progress in Material Handling Research: 2014

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

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    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

    Vertical or Horizontal Transport? - Comparison of robotic storage and retrieval systems

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    Autonomous vehicle-based storage and retrieval systems are commonly used in e-commerce fulfillment as they allow a high and flexible throughput capacity. In these systems, roaming robots transport loads between a storage location and a workstation. Two main variants exist: Horizontal, where the robots only move horizontally and use lifts for vertical transport and a new variant Vertical, where the robots can also travel vertically in the rack. This paper builds a framework to analyze the performance of the vertical system and to compare its throughput capacity with the horizontal system. We build closed-queueing network models for this that in turn are used to optimize the design. The results show that the optimal height-to-width ratio of a vertical system is around 1. As a large number of system robots may lead to blocking and delays, we compare the effect of two different robot blocking protocols on the system throughput: robot Recirculation and Wait-On-Spot. The Wait-On-Spot policy produces a higher system throughput when the number of robots in the system is small. However, for a large number of robots in the system, the Recirculation policy dominates the Wait-On-Spot policy. Finally, we compare the operational costs of the vertical and the horizontal transport system. For systems with one load/unload (L/U) point, the vertical system always produces a similar or higher system throughput, with a lower operating cost comp

    The impact of integrated cluster-based storage allocation on parts-to-picker warehouse performance

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    Order picking is one of the most demanding activities in many warehouses in terms of capital and labor. In parts-to-picker systems, automated vehicles or cranes bring the parts to a human picker. The storage assignment policy, the assignment of products to the storage locations, influences order picking efficiency. Commonly used storage assignment policies, such as full turnover-based and class-based storage, only consider the frequency at which each product has been requested but ignore information on the frequency at which products are ordered jointly, known as product affinity. Warehouses can use product affinity to make informed decisions and assign multiple correlated products to the same inventory ā€œpodā€ to reduce retrieval time. Existing affinity-based assignments sequentially cluster products with high affinity and assign the clusters to storage locations. We propose an integrated cluster allocation (ICA) policy to minimize the retrieval time of parts-to-picker systems based on both product turnover and affinity obtained from historical customer orders. We formulate a mathematical model that can solve small instances and develop a greedy construction heuristic for solving large instances. The ICA storage policy can reduce total retrieval time by up to 40% c
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