A U-Shaped Layout for a Manual Order Picking System

In manual order picking systems, order pickers walk or ride through a warehouse in order to collect items requested by customers. The performance of such a system is significantly dependent on its layout which determines the lengths of the order pickers\u27 tours and the corresponding picking times. Whereas for classic warehouse layouts all picking aisles are arranged in parallel to each other, in the warehouse layout presented here the picking aisles are arranged around a U-shaped central aisle. This layout has been developed for order picking systems in which slow-moving items are prevalent. A new routing strategy for such a warehouse is presented and an analytical expression for the expected tour length per picking order is derived. By comparing this estimation with those of routing schemes in classic warehouse layouts, it is demonstrated in which situations such U-shaped layouts allow for operating warehouses more efficiently

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

New solution procedures for the order picker routing problem in U-shaped pick areas with a movable depot

This paper develops new solution procedures for the order picker routing problem in U-shaped order picking zones with a movable depot, which has so far only been solved using simple heuristics. The paper presents the frst exact solution approach, based on combinatorial Benders decomposition, as well as a heuristic approach based on dynamic programming that extends the idea of the venerable sweep algorithm. In a computational study, we demonstrate that the exact approach can solve small instances well, while the heuristic dynamic programming approach is fast and exhibits an average optimality gap close to zero in all test instances. Moreover, we investigate the infuence of various storage assignment policies from the literature and compare them to a newly derived policy that is shown to be advantageous under certain circumstances. Secondly, we investigate the efects of having a movable depot compared to a fxed one and the infuence of the efort to move the depot

Feasibility of Warehouse Drone Adoption and Implementation

While aerial delivery drones capture headlines, the pace of adoption of drones in warehouses has shown the greatest acceleration. Warehousing constitutes 30% of the cost of logistics in the US. The rise of e-commerce, greater customer service demands of retail stores, and a shortage of skilled labor have intensified competition for efficient warehouse operations. This takes place during an era of shortening technology life cycles. This paper integrates several theoretical perspectives on technology diffusion and adoption to propose a framework to inform supply chain decision-makers on when to invest in new robotics technology

A multi-scenario analysis to improve layout efficiency

Logistics costs represent a large portion of overall costs. Companies in peripheral countries need to be additionally careful in streamlining them if they want to maintain their competitivity. This research is focussed on a plant belonging to an aerospace component supplier, and its purpose is to reduce the layout costs in one of its warehouses. Data was collected using documentation, archival records, informal interviews, and direct and participant observation. From 66 initial scenarios based on layout decisions, storage assignment policies and alternative picking routes, 44 were compared as these are the ones that fit the company reality. Findings showed that travelling distance could be reduced when the allocation of items in shelves follow their picking frequency and when Class-based storage with return routing policies is used. In parallel, it does not impact in a relevant way process time and the quality of the picking.info:eu-repo/semantics/submittedVersio

Evaluation of order picking systems using simulation

Sipari? toplama faaliyetleri, tedarik zinciri yönetiminde, hem üretim sistemleri açısından (montaj istasyonlarına alt parçaların tedarik edilmesi), hem de dağıtım i?lemleri açısından (mü?teri taleplerinin kar?ılanması) kritik rol oynamaktadır. Mü?teri sipari?lerindeki eğilimler, az sayıda ve yüksek miktarlarda sipari?lerin çok sayıda ve dü?ük miktarlarda sipari?lere dönü?tüğünü göstermektedir. Diğer yandan, talep edilen sipari? teslim süreleri ise her geçen gün kısalmaktadır. Bu deği?imler, i?letmelerin piyasada rekabet edebilmeleri için etkin ve esnek bir sipari? toplama sistemi benimsemelerini gerektirmektedir. Sipari? toplama süreci, tüm lojistik operasyonlarını ve mü?teriye sağlanan hizmet seviyesini büyük ölçüde etkilemektedir. Ayrıca, sipari? toplama süreci toplam depolama maliyetlerinin yarıdan fazlasını olu?turmaktadır. Bu nedenle, sipari? toplama faaliyetlerinin en etkin ?ekilde gerçekle?tirilmesi i?letmeler için büyük önem ta?ımaktadır. Bu çalı?manın amacı, sipari? toplama süresini kısaltarak, sipari? toplama etkinliğini arttırmaya yönelik deği?iklikler için sipari? toplama sistemini değerlendirmek ve geli?tirmektir. Sipari? toplama süresi, ürünlerin depolama alanlarından belirli bir mü?teri talebini kar?ılamak amacıyla toplanması süreci için geçen zamandır. Bu çalı?mada, ürünlerin depolama alanlarına atanma kararları ve rotalama metotları gibi kritik faktörlerin yanı sıra, daha önce gerçekle?tirilmi? çalı?malarda sıkça rastlanmayan depolama alanlarının ikmali problemi dikkate alınmı?tır. Bo?alan rafların yeniden doldurulması kararında, (S, s) envanter politikası uygulanmı?tır. Böylece, sipari? toplama sistemi dinamik olarak modellenmi?tir. Sipari? toplama performansını geli?tirmek için, bağlantı elemanları üreten bir firmanın ambarı temel alınarak olu?turulmu? hipotetik bir ambar üzerinde vii çalı?ılmı?tır. Ambara ait farklı benzetim modelleri olu?turulmu?, depolama ve rotalama politikalarının alternatif kombinasyonları geli?tirilerek bu benzetim modellerinde kullanılmı?tır. Elde edilen benzetim sonuçlarına göre, en küçük sipari? toplama süresini veren depolama ve rotalama politikası kombinasyonu belirlenmi?tir. Son olarak, benzetim sonuçları üzerinde bazı istatistiksel analiz metotları uygulanmı?tır Order picking activities play a critical role in supply chain management in terms of both production systems (supplying components to assembly operations) and distribution operations (meeting customer demands). Trends in customer orders reveal that orders are transformed from few-and-large orders to many-and-small ones. On the other hand, lead times of customer orders get consistently shorter. Because of these changes, companies need to adopt an effective and flexible order picking system in order to remain competitive in the market. Order picking affects both overall logistic operations and service level provided to customers. Additionally, order picking process constitutes more than half of the total warehousing cost. For these reasons, it is crucial for companies to design and perform an effective order picking process. The aim of this study is evaluating and improving of the order picking system so as to minimize the order retrieval time while increasing the picking efficiency. Order retrieval time can be defined as the time elapsed for the process of retrieving products from storage area to meet a specific customer demand. Besides the critical factors such as storage assignment decisions and routing methods, replenishment problem of the storage areas, which is rarely addressed in the previous studies, has been taken into consideration in this study. Replenishment of the empty storage locations has been conducted by using the (S, s) inventory policy. Thus, the order picking system was modeled as a dynamic system. A hypothetical distribution warehouse, based on the real life warehouse of a company specialized in production of fasteners, has been studied in order to improve the order picking performance. Alternative combinations of routing and storage policies have been developed. Moreover, different simulation models of the order picking process were constructed. In these models, proposed alternative storage and v routing policies were operated. According to the simulation results, the storage policy and routing policy combination which provides the shortest order retrieval time is determined. Finally, using simulation results, some statistical analysis methods have been implemented

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