Relative pre-positioning of storage/retrieval machines in automated storage/retrieval system to minimize expected system response time

This paper is focused on the control problem of determining the dwell point of an idle storage/retrieval (S/R) machine in an automated S/R system to improve the overall system service level as measured by the turnaround time of requests to the system. The emphasis of the paper is on the minimization of the expected response time over all retrieval and storage requests executed by the system. The model presented is developed under the operating condition that each machine serves several dedicated aisles of the system. The aisles are assumed to exist in the same region of the automated storage/retrieval system (AS/RS) and thus form a valid order S/R zone. A solution algorithm for determining the optimal dwell point location is developed. The paper assumes a dynamic environment where orders arrive over time and are to be serviced by the S/R machine. A dwell point or strategic point to pre-position the machine is to be determined whenever the machine becomes idle in anticipation of an incoming service request. A numerical example is provided to demonstrate how the technique can be used in an actual production setting to improve the overall order turnaround time.     

Expected travel time and optimal boundary formulas for a two-class-based automated storage/retrieval system

Our paper studies a two-class-based rectangular-in-time automated storage/ retrieval system (AS/RS). We present explicit formulas for the optima! boundary of the two storage areas as well as for the expected single command cycle time for an optimally designed rack. In the basic model each crane handles a single aisle. These formulas provide the designer with a full picture of the quantitative effects of the various factors (i.e., access frequencies of the two storage areas, and dimensions of the rack) on the optimal boundary of the two storage areas and the achievable cycle lime in the warehouse. We also develop expected travel time formulas for the dual command AS/RS with two-class-based storage policies and obtain the optimal boundary with a one-dimensional search procedure. Similar developments (i.e., expected travel time formulas and optimal boundary search procedures) are discussed for AS/RS with a single command policy but with each crane handling multiple aisles.     

Order batching algorithms and travel-time estimation for automated storage/retrieval systems

In this paper we present heuristics and analytical models for the order batching problem. Orders are batched into tours such that the total travel time is minimized. Four heuristics are developed for the order batching problem, for which no exact solution exists. All heuristics are based on the time-saving criterion of combining two or more orders in a single tour rather than processing them one order at a time. Among the heuristics that are presented, the SL algorithm has the best performance. An analytical model is developed to estimate the travel time of the S/R machine as a function of the number of locations to be visited and the physical specifications of the structure. Expressions for upper and lower bounds for travel time are presented.     

Relative pre-positioning of storage/retrieval machines in automated storage/retrieval systems to minimize maximum system response time

In this paper, the problem of pre-positioning a storage/retrieval (S/R) machine in an automated storage/retrieval system (AS/RS) when the machine is idle is addressed. The objective of the pre-positioning strategy is to minimize the maximum response time to service incoming requests into the AS/RS. A model is developed under the operating condition that each machine can serve one or multiple dedicated aisle(s) of the system. The aisles are assumed to exist in the same region of the AS/RS and thus form a valid order storage/retrieval zone. A solution algorithm for determining the optimal dwell point or location is developed. The paper assumes a dynamic environment where orders arrive over time and are to be serviced by the S/R machine. A dwell point or strategic point to pre-position the machine is to be determined whenever the S/R machine becomes idle in anticipation of an incoming service request. A numerical example is provided to demonstrate how the technique can be used in an actual production setting to improve the overall order turnaround time.     

A bi-directional flow-rack automated storage and retrieval system for unit-load warehouses

Flow-rack is a multi-deep rack containing multi-row and multi-column slope bins. Traditionally, bins slope in the same direction in a flow-rack to make unit-loads slide from the storage face to the retrieval face driven by gravity, which cause unit-loads are stored to the storage face and retrieved from the retrieval face. In this paper, a bi-directional flow-rack (BFR) is designed, in which bins in adjacent columns slope to opposite directions. In each side of a BFR, unit-loads are stored in half of the bins and retrieved from the other half. Therefore, dual-command (DC) operations could be simultaneously performed on both faces and blocking unit-loads are re-stored to available bins on the same face directly. We develop a travel time model for BFR systems, which provides the throughput baseline for different configurations of BFR. A DC operation generation method is introduced for BFR systems. Simulation experiments are conducted to evaluate the effectiveness of the BFR travel time model, to compare the throughput performance between BFR and SFR systems and to evaluate the performance of the proposed DC operation generation method.     

Interleaving models for the analysis of twin shuttle automated storage and retrieval systems

A system of state equations is formulated for describing the dynamic behaviour of the queue of storage and retrieval transactions in a storage aisle served by twin shuttle storage and retrieval (S/R) machines. Using estimates of order picking cycle times in conjunction with storage and retrieval transaction demand levels, an estimate of the probability distribution of storage queue states is derived for a given storage aisle. System performance measures under an opportunistic interleaving discipline including S/R machine utilization, transaction queue lengths, average cycle times and expected transaction waiting times are approximated using the state probability distribution. The modelling tools are demonstrated using sample problems where the performance of twin versus single shuttle systems is contrasted for alternative combinations of storage and retrieval machine travel speeds, storage rack configurations, and transactions demand scenarios.     

An expert system based controller for an automated storage/retrieval system

Expert systems have demonstrated their ability to solve problems of a specific domain and achieve quality performance. The technology has been applied in numerous engineering areas. In this paper, an expert system based AS/RS controller, ECSSIM, is presented. The system plans a control strategy based on the long term system characteristics. However, the system alters the control strategy tactically according to the short term control needs. The system performed very well particularly at high demand levels. It also demonstrated its capability of sensing poor control strategies, and tactically compensate for the strategy selection error.     

An efficient cycle time model for autonomous vehicle storage and retrieval systems

A computationally efficient cycle time model for conceptualizing autonomous vehicle storage and retrieval systems and comparing their performance with crane-based automated storage and retrieval systems is presented. The model is based on an iterative computational scheme exploiting random storage assumptions and queuing model approximations. Relative to earlier models, the procedure scales up efficiently for large problems thereby enabling more extensive search of a design solution space. Simulation based validation studies suggest that model accuracy is adequate for system conceptualization. The procedure is demonstrated using realistically sized sample problems.     

Modelling an automated storage and retrieval system using Petri nets

We investigated the feasibility of using stochastic Petri nets (SPNs) to describe the behaviours of automated storage/retrieval systems as well as to evaluate the performance of different control policies of such systems. SPNs have been studied in the past 2 decades, and have become a powerful tool in modelling concurrent and distributed systems that exhibit synchronization and contention of shared resources. It appeared that some important characteristics of AS/RS could be well modelled with SPNs. The SPN is a graph-based tool suitable for modelling systems (manufacturing, computer, biological, etc.). It can be used to model a system at different levels of abstraction. In this study, the efficiency, control rules, bay assignment, and many other performance issues associated with AS/RS have been studied in detail using SPN models. SPNs are shown to be equivalent to the stochastic processes in which embedded Markov chains can be recognized. In addition, a stochastic Petri net package, SPNP, was adopted to solve the reachability trees from which an embedded Markov chain was generated. Finally, the performance of those systems of our interest was evaluated. The unique features and flexibility of SPNs are presented. Furthermore, the SPN models for different control algorithms of an AS/RS are discussed with examples.     

Simulation study of an automated storage/retrieval system

In this paper we present a simulation study of an automated storage/retrieval system and examine a wide variety of control policies. We compare several storage location assignment policies. For the class-based storage policy, we apply a recent algorithm that enables us to evaluate the trade-off between storage space requirements and travel times. We also study a new storage location policy which combines low storage space requirements with short mean travel times. Furthermore, we study the sequencing of storage and retrieval requests whereby we focus on the trade-off between efficient travel of the S/R machines and response time performance.     

Performance analysis for automated storage and retrieval systems

Automated storage and retrieval (AS/R) systems have had a dramatic impact on material handling and inventory control in warehouses and production systems. A unit-load AS/R system is generic and other AS/R systems represent its variations. Common techniques that are used to predict performance of a unit-load AS/RS are a static analysis or computer simulation. A static analysis requires guessing a ratio of single cycles to dual cycles, which can lead to poor prediction. Computer simulation can be time-consuming and expensive. In order to resolve these weaknesses of both techniques, we present a stochastic analysis of a unit-load AS/RS by using a single-server queueing model with unique features. To our knowledge, this is the first study of a stochastic analysis of unit-load AS/R systems by an analytical method. Experimental results show that the proposed method is robust against violation of the underlying assumptions and is effective for both short-term and long-term planning of AS/R systems.     

A storage assignment policy in a man-on-board automated storage/retrieval system

This paper deals with a man-on-board automated storage/retrieval system where each customer order consists of a number of different items and is picked one at a time. For the system the problem examined is to allocate storage locations dedicatedly to items so that the total travel time required to pick all the given orders per period is minimized. The problem is shown to be formulated as a variant of the generalized assignment model. A heuristic for the storage layout problem is developed based on the group technology concept considering both order structure and frequency. Through the heuristic, close relationships between items are identified from the order structure, and then based on the relationships the items are compelled to be stored closely in the storage rack following a space-filling curve. Experimental results are provided to describe the performance of the heuristic     

Optimal routing in an automated storage/retrieval system with dedicated storage

We address the sequencing of requests in an automated storage/retrieval system with dedicated storage. We consider the block sequencing approach, where a set of storage and retrieval requests is given beforehand and no new requests come in during operation. The objective for this static problem is to find a route of minimal total travel time in which all storage and retrieval requests may be performed. The problem of sequencing a list of retrievals is equivalent to the Traveling Salesman Problem (TSP), and thus NP-hard in general. We show that the special case of sequencing under the dedicated storage policy can be solved in polynomial time. The results apply to systems with arbitrary positions of the input and output stations. Tlus generalizes the models in the literature, where only combined input/output stations are considered. Furthermore we identify a single command area in the rack. At the end we evaluate the model against heuristic procedures.     

Intelligent control schemes for automated storage and retrieval systems

A new information system approach to the operational controls of automated storage and retrieval systems (AS/RS) is developed and examined. This approach is based on artificial intelligence, state-operator framework for problem solving. Gradually increasing the information level, several operational goal functions are identified for an industrial unit-load food produce AS/RS. These functions use real-time statistical interpolations to select the desired storage and retrieval bins. As a result the AS/RS response adapts itself to stochastic perturbations in the system conditions. Experimental evaluations using multiple variance analysis technique and detailed simulations have shown that the proposed dynamic approach is superior to the common industrial control method currently used in those industrial systems characterized by batch arrivals (and retrievals) of the UL's and non-stationary demand patterns, These evaluations further suggest that improved performance is realized with the increase in the information level. The operational control scheme developed in this paper appears to be an excellent control alternative for unit-load AS/RSs. This is due to its limited computational requirements and the augmented productivity as demonstrated here for a real case study.     

Sequencing approaches for multiple-aisle automated storage and retrieval systems

Automated storage and retrieval systems (AS/RS) are used in high velocity distribution centres to provide accurate and fast order processing. While almost every industrial system is comprised of many aisles, most of the academic research on the operational aspects of AS/RS is devoted to single-aisle systems, probably due to the broadly accepted hypothesis proposing that an m aisles system can be modelled as m 1-aisle independent systems. In this article, we present two multi-aisles sequencing approaches and evaluate their performance when all the aisles are managed independently first, and then in a global manner. Computational experiments conducted on a multi-aisle AS/RS simulation model clearly demonstrate that a multi-aisle system cannot be accurately represented by multiple single-aisle systems. The numerical results demonstrate that, when dealing with random storage, globally sequencing multi-aisle AS/RS leads to makespan reductions ranging from 14 to 29% for 2- and 3-aisle systems, respectively.     

Multi-shuttle automated storage/retrieval systems

Multi-shuttle automated storage/retrieval systems have been developed for use in factories and distribution centers because they are more efficient than single-shuttle systems (owing to less empty travel). This improved efficiency results in more agile support (flexible response, less waiting time, etc.) for the production system the storage/retrieval system serves. In this paper we develop analytical models to estimate the throughput in multi-shuttle systems. Throughput improvements greater than 100% are illustrated when triple-shuttle systems are compared with single-shuttle systems.     

Closed form models for determining the optimal dwell point location in automated storage and retrieval systems

This paper examines the problem of where a storage/retrieval machine should reside, or dwell, when an automated storage and retrieval system (AS/RS) becomes idle to minimize the expected value of the next transaction time. After a review of the relevant literature on AS/RS dwell point strategies, this paper proposes several analytical models of these expected response times of the AS/RS based on the relative locations of the input and output ports of the AS/RS. It uses a continuous rack approximation to provide analytical models of the dwell point location problem. These models provide closed form solutions for the dwell point location in an AS/RS. Extensions are made to consider AS/RS with a variety of configurations including multiple input and output ports. These models not only provide solutions to the dwell point location problem, but they provide considerable insight into the nature of this problem, which is particularly valuable when the requirements facing the AS/RS are uncertain.     

The impact of acceleration/deceleration on travel-time models for automated storage/retrieval systems

In this note we propose a travel-time model of automated storage/retrieval (S/R) machines by considering the speed profiles that exist in real-world applications. Compact forms of expected travel-times under randomized storage conditions have been determined for both single and dual command cycles.     

On sequencing policies for unit-load automated storage and retrieval systems

Automated Storage and Retrieval System (AS/RS) performance highly depends on the characteristics of the mechanical equipment. However, once the system has been physically implemented, achieving its maximum efficiency depends on the way the system is operated. This paper shows that request sequencing (i.e. planning the order in which storage and retrieval requests are performed) is of paramount importance in AS/RS performance. This paper reviews and adapts the most popular storage and sequencing policies to dynamic contexts, and then it proposes a ‘sequencing mathematical model’ (SMM) to simultaneously solve the sequencing and storage location problems. Extensive computational results based on a thorough simulation experiment plan confirm that performing the requests in the right sequence can have a positive impact on AS/RS performance. Our results show that the proposed SMM regularly outperforms other methods. When used in a dynamic context, the proposed SMM may yield up to a 25% reduction in average travel-time compared to the situation where a no-sequencing method is applied.     

Throughput bounds for miniload automated storage/retrieval systems

To compute miniload system throughput, the distribution of the pick times is needed. Unfortunately, during the design phase, only partial information may be available such as the mean pick time. In this paper, we determine tight upper and lower bounds on throughput for several different types of partial information. We also give numerical examples to show how to apply the bounds.