Enhancing performance in order picking processes by dynamic storage systems

Increasing productivity and reducing labour cost in order picking processes are two major concerns for most warehouse managers. Particularly picker-to-parts order picking methods lead to low productivity as order pickers spend much of their time travelling along the aisles. To enhance order picking process performance, an increasing number of warehouses adopt the concept of dynamic storage where only those products needed for the current order batch are dynamically stored in the pick area, thereby reducing travel time. Other products are stored in a reserve area. We analyse the stability condition for a dynamic storage system with online order arrivals and develop a mathematical model to derive the maximum throughput a DSS can achieve and the minimum number of worker hours needed to obtain this throughput, for order picking systems with a single pick station. We discuss two applications of dynamic storage in order picking systems with multiple pick stations in series. In combination with simulation modelling, we are able to demonstrate that dynamic storage can increase throughput and reduce labour cost significantly.     

Determining the number of zones in a pick-and-sort order picking system

In this study we consider a pick-and-sort order picking system, in which batches of orders are picked simultaneously from different (work) zones by a group of order pickers. After picking, the orders are transported by a conveyor to a next station for consolidation and packing. Packing can only occur when an order has been picked completely. For a given number of workers, each assigned to a single zone, a larger number of zones reduces pick time (since travel time reduces), but increases waiting time for completion at the packing stations, because more partial batches needing assembly arrive at the packing stations. Our aim is to determine the optimal number of zones such that the total (picking and packing) time to complete a batch is minimised. We solve this problem by optimally assigning items to pick routes in each zone. We illustrate the method with data taken from a distribution centre of one of the largest online retailers in The Netherlands.     

The use of bucket brigades in zone order picking systems

As the transactions through electronic commerce and TV home shopping increase, the warehouses often receive a large amount of small orders to be picked within tight time windows. One of the important warehousing activities is order picking, the process of retrieving a number of items from warehouse storage to meet a number of independent customer orders. This paper examines a new order picking method, bucket brigade order picking (BB picking). Bucket brigade is a way of coordinating workers who progressively perform a set of operations on a flow line. In the BB picking system, a worker performs operations on an order until the next worker downstream takes it over; then goes back to the previous worker upstream to take over a new order. We discuss distinct characteristics in order picking systems when bucket brigades are applied. We identify some efficiency losses under the BB picking and present a new BB picking protocol to improve the performance of order picking systems. The new BB picking is compared with the existing BB picking and zone picking through simulation experiments.     

Ergonomic workplace design in the fast pick area

The aging society in many developed countries has made an ergonomic workplace design to an important topic among researchers and practitioners alike. We investigate the workplace design for order pickers that manually collect items from the shelves of a warehouse. Specifically, we treat the storage assignment, i.e., the placement of products in shelves of different height, and zoning, i.e., the partitioning of the storage space into areas assigned to separate pickers, in the fast pick area of a warehouse. A fast pick area unifies the most fast-moving items in a compact area, so that workers are relieved from unproductive travel, but face extraordinary ergonomic risks due to the frequent repetition of picking operations. Concerning the health of (aged) workers, it is crucial to reduce such risks. Thus, we define a combined ergonomic storage assignment and zoning problem with the objective of minimizing the maximum ergonomic burden among all workers. This problem is formalized, and two construction heuristics and a tabu search procedure are proposed. Our results show that neglecting ergonomic aspects and only focusing on picking performance leads to much higher ergonomic risks of the workforce.

     

多人拣选系统拥堵的马尔科夫建模与仿真研究

目的 为了降低拣选系统拥堵率提高应急物资的运输效率,文中提出一种基于马尔科夫的多人拥堵模型。方法 分别构建窄通道货位单件拣选和货位多件拣选情况下的马尔科夫状态转移矩阵,求解平稳分布,获得拣选概率与拥堵率的函数关系式,并通过仿真分析不同因素变化对拥堵率的影响。结果 研究发现在货位单件拣选情况下,拣选概率取值为0.3左右时,系统拥堵率达到峰值,之后随拣选概率的增大而减小;在货位多件拣选情况下,拣选概率与系统拥堵率呈正相关,系统拥堵率随着拣选概率的增加而增加。结论 在实际拣选作业中,为了降低系统拥堵率,货位单件拣选应尽量避免拣选概率在0.3左右;货位多件拣选应尽量降低拣选概率。     

Optimal layout in low-level picker-to-part systems

The paper presents an analytical approach to layout design of the picking area in low-level, picker-to-part systems using COI (cube per order index)-based and random storage policies. The layout of the picking area is one of the major issues in increasing picking system productivity, i.e. in reducing the time required to complete a given set of orders, and must take account of the inter-relationship between the main operating policies, i.e. storage, routing and batching. The main system parameters affecting the layout design are the total length of the picking aisles, the number of pick stops per tour and the shape of the COI-based ABC curve. A formula that relates the optimal number of aisles to the above parameters will be presented, together with the increase in the expected tour distance stemming from the adoption of a non-optimal number of aisles. The study thus provides a comprehensive framework for layout design.     

Robotics in order picking: evaluating warehouse layouts for pick,place, and transport vehicle routing systems

Motivated by recent technological advances in mobile robotics, this paper explores a novel approach for warehouse order picking. In particular, this work considers two types of commercially available mobile robots – one that can grasp items from a shelf (a picker) and another (a transporter) that can quickly deliver all items from the pick list to the packing station. A new vehicle routing problem is defined which seeks to minimise the time to deliver all items from a pick list to the packing station, a problem termed the pick, place, and transport vehicle routing problem. A mixed integer linear programming formulation is developed to answer three related research questions. First, what combination of picker and transport robots is required to obtain performance exceeding traditional human-based picking operations? Second, how should the composition of the robot fleet be altered to affect the greatest performance improvements? Finally, what are the impacts of warehouse layout designs when coordinated mobile robots are deployed? An extensive numerical analysis reveals that, (1) increasing the number of cross aisles decreases system performance; (2) centrally located packing stations improve system performance; and (3) the average distance from each pick location to the packing station and the average distance between pick locations are effective metrics for identifying specific fleet modifications that are likely to yield system improvements.     

Pick‐and‐Place Assembly of Single Microtubules

Intracellular transport is affected by the filament network in the densely packed cytoplasm. Biophysical studies focusing on intracellular transport based on microtubule–kinesin system frequently use in vitro motility assays, which are performed either on individual microtubules or on random (or simple) microtubule networks. Assembling intricate networks with high flexibility requires the manipulation of 25 nm diameter microtubules individually, which can be achieved through the use of pick‐and‐place assembly. Although widely used to assemble tiny objects, pick‐and‐place is not a common practice for the manipulation of biological materials. Using the high‐level handling capabilities of microelectromechanical systems (MEMS) technology, tweezers are designed and fabricated to pick and place single microtubule filaments. Repeated picking and placing cycles provide a multilayered and multidirectional microtubule network even for different surface topographies. On‐demand assembly of microtubules forms crossings at desired angles for biophysical studies as well as complex networks that can be used as nanotransport systems.     

The effect of warehouse cross aisles on order picking efficiency

This paper investigates the effects of adding cross aisles to the layout of an order consolidation warehouse, with respect to order picking efficiency. Intuitively, cross aisles provide greater flexibility in the routing of order pickers, thus providing shorter order picking travel distances. However, this effect may be negated when the number of cross aisles becomes excessive, as the cross aisles themselves must be traversed in order to reach the required items. A shortest path pick sequencing model is developed which allows for any number of cross aisles in the warehouse. The optimal routing is computed for a large number of randomly generated picking requests, over a variety of warehouse layout and order picking parameters. The results are used to characterize the optimal number of warehouse cross aisles, as well as the conditions under which cross aisles generate the greatest benefit.     

Exploring the role of picker personality in predicting picking performance with pick by voice,pick to light and RF-terminal picking

Order pickers and individual differences between them could have a substantial impact on picking performance, but are largely ignored in studies on order picking. This paper explores the role of individual differences in picking performance with various picking tools (pick by voice, RF-terminal picking and pick to light) and methods (parallel, zone and dynamic zone picking). A unique realistic field experiment with 101 participants (academic students, vocational students and professional pickers) is employed to investigate the influence of individual differences, especially the Big Five personality traits, on picking performance in terms of productivity and quality. The results suggest that (PbV) performs better than RF-terminal picking, and that Neuroticism, Extraversion, Conscientiousness and the age of the picker play a significant role in predicting picking performance with voice and RF-terminals. Furthermore, achieving higher productivity appears to be possible without sacrificing quality. Managers can increase picking performance by incorporating the insights in assigning the right pickers to work with a particular picking tool or method, leading to increased picking performance and reduced warehousing costs.     

Routing orderpickers in a warehouse: a comparison between optimal and heuristic solutions

In this paper the problem of finding efficient orderpicking routes is studied for both conventional warehouses, where pickers have a central depot for picking up and depositing carts and pick lists, and modern warehouses, where orderpicking trucks can pick up and deposit pallets at the head of every aisle without returning to the depot. Such environments can be found in many warehouses where paperless picking is performed from pallet locations with pickers having mobile terminals receiving instructions one by one. In order to find orderpicking routes with a minimal length in both the situations of a central depot or decentralized depositing, we extend the well-known polynomial algorithm of Ratliff and Rosenthal [1] that considered warehouses with a central depot. In practice, the problem is mainly solved by using the so-called S-shape heuristic in which orderpickers move in a S-shape curve along the pick locations. The performance of the new algorithm and the S-shape heuristic are compared in three realistic orderpicking systems: (1) narrow-aisle high-bay pallet warehouse; (2) picking in shelf area with decentralized depositing of picked items; and (3) conventional orderpicking from wide-aisle pallet locations. The new algorithm gives a reduction in travel time per route of between 7 and 34%. It turns out that the reduction in travel time strongly depends on the lay-out and operation of the warehouse.     

Order Picking In An Aisle

A classical order picking problem is the case where items have to be picked from both sides of an aisle and the picker cannot reach items on both sides without changing position. Hence the picker must cross the aisle one or more times. An efficient optimal algorithm is developed and shown to yield policies with up to 30% savings in travel time over commonly used policies. It is also shown that, for most practical aisle widths, it is significantly more efficient to pick both sides of the aisle in the same pass (a traversal policy) rather than pick one side and then pick the other side (a return policy) unless the pick densities are greater than 50%. All the algorithms presented here can be implemented in real time on a microcomputer.     

A model for warehouse layout

This paper describes an approach to determine a layout for the order picking area in warehouses, so that the average travel distance for the order pickers is minimized. We give analytical formulas that can be used to calculate the average length of an order picking route under two different routing policies. The optimal layout can be determined by using these formulas as the objective function in a nonlinear programming model. The optimal number of aisles in an order picking area appears to depend strongly on the required storage space and the pick list size.     

Enhancing the order picking process through a new storage assignment strategy in forward-reserve area

This paper reexamines the order picking process in a warehouse facing the challenges that e-commerce brings about and which are characterised by a very large number of small sized orders and returns. Implementing effective storage assignment strategies combined with efficient batching, in this context, is very fundamental to keep the warehouse’s responsiveness and order completion times up to the standards. This paper investigates a new storage assignment strategy, initially implemented by a large shoes and footwear wholesaler, to enhance the performance of the order picking process in its warehouses. The impact of this new storage assignment strategy on the performance of the order picking process is analysed via simulation. The performance of the system, measured in terms of total picking time as well as order lead time while taking congestion into account, is compared to the cases where conventional storage assignment strategies are implemented. A full factorial design is set up and the simulation output is statistically analysed. The results of this analysis are reported and thoroughly discussed. Attending to the results, the proposed strategy presents a remarkable potential to shorten total picking travel distances and order completion time and consequently customer satisfaction.     

The use of time series forecasting in zone order picking systems to predict order pickers’ workload

In order to differentiate from competitors in terms of customer service, warehouses accept late orders while providing delivery in a quick and timely way. This trend leads to a reduced time to pick an order. This paper introduces workload forecasting in a warehouse context, in particular a zone picking warehouse. Improved workforce planning can contribute to an effective and efficient order picking process. Most order picking publications treat demand as known in advance. As warehouses accept late orders, the assumption of a constant given demand is questioned in this paper. The objective of this study is to present time series forecasting models that perform well in a zone picking warehouse. A real-life case study demonstrates the value of applying time series forecasting models to forecast the daily number of order lines. The forecast of order lines, along with order pickers’ productivity, can be used by warehouse supervisors to determine the daily required number of order pickers, as well as the allocation of order pickers across warehouse zones. Time series are applied on an aggregated level, as well as on a disaggregated zone level. Both bottom-up and top-down approaches are evaluated in order to find the best-performing forecasting method.     

Order picking in a parallel-aisle warehouse with turn penalties

In many real-life routing problems, incorporating the negative effects of turns is an important, but often overlooked aspect. This is especially true for order picking in warehouses, where making the turns not only decreases the picking efficiency by reducing the speed of the vehicle, but it also results in other unquantifiable effects such as vehicle tipovers, increased congestion and increased risk of collision with pedestrians or other vehicles. In this paper, we consider the order picking problem in a parallel-aisle warehouse by taking into account the number and effect of the turns. In particular, we show that the problem of minimising the number of turns, minimising travel time under turn penalties, the biobjective problem that involves turn and travel time minimisation as separate objectives, and the triobjective problem with U-turn minimisation as a third objective can all be solved in polynomial time. Our computational results show that the algorithms we develop can generate the corresponding Pareto front very quickly, and significantly outperform heuristic approaches used in practice.     

最小控制递归平均算法对光纤声音传感系统的降噪作用

为了解决恶劣环境下分布式光纤声音传感系统的声音还原问题,搭建了一种基于改进最小控制递归平均(IMCRA)算法的多通道光纤声音传感系统。采用Sagnac和Mach-Zehnder复合光路结构,以单模光纤作为传感单元拾取声音信号,借助光开关实现了多通道信号采集,并通过改进最小控制递归平均算法对声音信号进行降噪、还原及增强处理。实验结果表明:该系统可在长为4km的传感光纤上实现对单音信号和语音信号的多通道扫描拾取,并能够在复杂情况下实现对语音信号信噪比的有效提升,为光纤声音传感系统在恶劣环境下的应用提供了一种新途径。     

气动软体采摘机械手设计及实验研究

针对传统刚性采摘机械手适用范围小、环境适应性差及对果蔬损伤大等问题,设计了一种面向沙果采摘的刚柔耦合气动软体采摘机械手。根据沙果的结果特点以及采摘要求,确定了六指包裹式采摘形式。以龙丰果为例,建立了采摘机械手软体手指弯曲角度计算模型,确定了单指的弯曲角度;通过3种硅胶材料的拉伸对比实验,选定HY-E620型硅胶作为软体手指的材料;开展了多种结构对软体手指弯曲性能影响的ABAQUS有限元仿真分析,确定了较优的结构;利用实验测定了不同驱动气压条件下单根软体手指弯曲角度与输出力的对应关系,并在0.08 MPa驱动气压下对多种水果进行三指抓取实验,验证了软体手指结构的合理性。最后,试制了六指包裹式气动软体采摘机械手,并分别对沙果、苹果、梨和橘子等进行了采摘实验。结果表明：所设计的采摘机械手不仅对含3~6个果实的成串沙果的采摘成功率达到80％,还可采摘苹果、梨和橘子等类球形水果,具有一定的通用性,可为水果采摘机械手的设计与研究提供新思路。     

Material handling improvement in warehouses by parts clustering

A major part of warehouse operations is related to the collection of parts from the warehouse which is called the Order Picking Problem. To improve order picking operations, the total travel distance and generally picking time must be reduced. In this paper, a two-level approach is proposed that determines the locations of parts in the warehouse. The first step clusters parts into part families. Four different clustering methods based on principal component analysis, singular value decomposition and Two-Step Cluster Component are applied. In the second step, four different heuristics are proposed to determine the locations of parts. In addition to the minimisation of travel distance, we also consider the minimisation of the total congestion in aisles due to multiple workers. The proposed algorithms also consider the interactions between part families to minimise intergroup movements. As a result of the implementation, we achieved more than 40% reduction in material handling compared to the current set-up of the warehouse. The applied algorithms can easily be modified to be used for warehouses with different configurations. The algorithms utilised in this case study can be helpful to researchers to become familiar with new heuristics, as well as practitioners to design improved warehouses.     

Evaluating order picking performance trade-offs by configuring main operating strategies in a retail distributor: A Design of Experiments approach

Warehouse design has become important due to its impact on service to customers and total logistics costs. Order picking is the key activity of a warehouse and an appropriate design will directly affect its overall performance. The increasing complexity of warehouses means that the main operating strategies such as storage location assignment, batching and routing need to be considered simultaneously. A Design of Experiment approach aided by Discrete Event Simulation could help to meet these new picking design process requirements, especially when various performance measures need to be compared. Some of the trade-offs that managers must keep in mind when designing order picking systems are shown, describing a single-case study carried out at a retail distributor.