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

Simulation Analysis of Mixed Bulk and Rack Warehouse Systems

With the growth of the supply chain and increased customer demand, warehouse operation has become very important. One of the critical functions of warehouse operation is to have a warehouse layout such that the day-to-day operations enable on-time delivery. Poor warehouse design can lead to ineffective warehouse space utilization and incur the cost associated with inefficient operations. The purpose of this study is to develop an analysis tool that enables companies to identify the appropriate mix of bulk and rack storage locations to utilize warehouse space effectively. A simulation-based methodology is used to determine the optimal mix of racks and bulk lanes for a warehouse layout considering inventory quantities and turnover rates. Evaluation parameters include the number of racks and storage locations, the number of bulk lanes and lane depth, and the velocity mapping of products based on demand. The experimental results demonstrate the trade-offs of key performance metrics for various system configurations

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

Throughput Analysis of Manual Order Picking Systems with Congestion Consideration

Throughput in manual order picking systems with narrow aisles suffers from congestion as pickers cannot pass each other. Only few models incorporate congestion but they have very strict assumptions. In this work, queueing theory is used to analyze systems with traversal routing as well as different storage policies. The models are able to estimate throughput for many alternative designs in a relatively short amount of time. New guidelines for narrow-­aisle order picking systems are introduced

DYNAMIC SIMULATION ANALYSIS FOR VARIOUS NUMBERS OF ORDERS IN AN INTEGRATED CAR-MANUFACTURING WAREHOUSE

The order-picking process in a warehouse is critical in managing customer orders, especially in retail stores. It is expensive because fulfilling online orders takes up to 70% of all warehouse activities. Procedures in order picking, including different route selection schemes, can significantly increase yield and reduce costs. The research shows that a suitable routing method can reduce the travel time of the order picker to fulfill the order. However, the number of orders may vary. This paper presented a dynamic simulation analysis based on a real scenario of a various number of orders in an integrated car manufacturing warehouse. The simulation reduced the travel time of the voters by about 44.89%. This simulation model helps to visualize the potential reduction in customer waiting times, leading to increased customer satisfaction

Developing a Decision Support Tool for Increased Warehouse Picking Efficiency

Problem description: Warehousing is central in order to achieve a competitive supply chain, and considered essential for the success, or failure, of businesses today. In general, warehouses account for a large share of the company logistics costs. Consequently, there is a need for warehouses to operate smoother, faster and more accurate. Within warehousing, the most labor-intensive and costly warehouse operation is order picking, this is mainly due to the large amount of travelling involved. All articles included in this study agree that order picking account for at least 50 percent of warehouses' total operating costs. Warehouses thus carry great potential to justify the expenses they bring through reducing the time spent on activities that are not value adding. Purpose: The overall goal in this thesis is to provide guidance for how a warehouse can operate more efficient by improving its picking performance, which also includes reviewing the closely interlinked warehouse operations storage allocation and routing. Research questions: How can a decision support tool for reviewing the choices of storage allocation, order picking, and routing methods in manual warehouse operations be put together in a structured way? Which features should be considered in the decision support tool for choosing methods for improving warehouse operations? Methodology: The guidance for improved picking performance was framed into a decision support tool building on a thorough review and analysis of the research available in the area. A case study on picking efficiency was conducted in order to create a deep understanding for the issues and challenges that prevail in warehousing, and also to ensure that the final recommendations and the answers to the research questions have good support in academia. Once the tool was created, an illustrative example was used to demonstrate the use of the tool on a more detailed level and to test its comprehensibility and usability. Conclusions: In many areas, the resulting tool manages to provide unequivocal guidance for how to improve a warehouse’ picking operations. Multiple features are identified as important for the decision process; among those are demand skewness, seasonality among different SKUs, total demand variation and pick list size. Company objectives and priorities were also identified as a central feature due to the interrelatedness of the decisions connected to picking and their well-known tradeoffs. The research is however sometimes scarce, and further studies need to be carried-out in order to complement and level the strength of the tool.Problembeskrivning: Lagerverksamhet utgör en central del i att uppnå en konkurrenskraftig försörjningskedja och betraktas som direkt avgörande för ett företags framgång, eller utebliven sådan. Det är en dyr verksamhet, och en stor del av ett företags totala logistikkostnader kan hänvisas direkt till lagret. Följaktligen finns det ett behov för lager att prestera jämnare, snabbare och mer precist. Orderplockning är den tveklöst kostsammaste och mest resurskrävande lageraktiviteten. Den huvudsakliga anledningen är att orderplockning till stor del består av transporter mellan platser, vilket inte i sig tillför något värde och därmed enbart är resurskrävande. Alla vetenskapliga artiklar som är inkluderade i studien är eniga om att minst 50 procent av ett typiskt lagers driftkostnader kan härledas till orderplock. Lagret har därmed stor potential att rättfärdiga sina kostnader, genom att reducera den andel tid och resurser som läggs på icke värdeskapande aktiviteter. Syfte: Det övergripande målet med uppsatsen är att skapa vägledning för hur lager kan öka sin effektivitet genom att förbättra sina plockprocesser. Detta inkluderar även de närliggande beslutsområdena lagerplatsallokering och ruttplanering. Forskningsfrågor: Hur kan ett beslutsverktyg för att granska metodval för lagerplatsallokering, orderplockning och ruttplanering vid manuell lagerverksamhet sättas ihop på ett strukturerat sätt? Vilka egenskaper bör beaktas i ett beslutsverktyg för att välja metoder som förbättrar lagerverksamheten? Metod: Beslutsverktyget skapades utifrån en grundlig genomgång samt analys av den forskning som finns inom området. En fallstudie om effektivisering av plockhantering genomfördes med syftet att skapa en djupgående förståelse för de problem och utmaningar som förekommer i en lagerverksamhet, liksom att säkerställa att de slutgiltiga rekommendationerna och svaren på forskningsfrågorna var väl förankrade i akademin. När verktyget var skapat användes ett illustrativt exempel för att demonstrera dess användning på en detaljerad nivå, samt för att testa hur lätt det är att förstå och använda. Slutsats: Beslutsverktyget som skapats lyckas ge tydliga rekommendationer och vägledning inom många områden för hur ett lagers plockprocesser kan förbättras. Flera egenskaper identifieras som särskilt viktiga att beakta i beslutsprocessen; bland annat skevhet i efterfrågan, säsongsförknippad efterfrågan mellan olika lagerplatsenhet, total variation i efterfrågan samt längden på plocklistorna. Företags egna mål och prioriteringar identifieras också som centrala i beslutsverktyget eftersom alla beslut är tätt sammanvävda och generellt innebär ständiga kompromisser. Inom flera områden relaterade till plockhantering visade sig forskningen emellertid vara otillräcklig, och ytterligare studier krävs för att stärka beslutsverktyget

Integrated Models and Tools for Design and Management of Global Supply Chain

In modern and global supply chain, the increasing trend toward product variety, level of service, short delivery delay and response time to consumers, highlight the importance to set and configure smooth and efficient logistic processes and operations. In order to comply such purposes the supply chain management (SCM) theory entails a wide set of models, algorithms, procedure, tools and best practices for the design, the management and control of articulated supply chain networks and logistics nodes. The purpose of this Ph.D. dissertation is going in detail on the principle aspects and concerns of supply chain network and warehousing systems, by proposing and illustrating useful methods, procedures and support-decision tools for the design and management of real instance applications, such those currently face by enterprises. In particular, after a comprehensive literature review of the principal warehousing issues and entities, the manuscript focuses on design top-down procedure for both less-than-unit-load OPS and unit-load storage systems. For both, decision-support software platforms are illustrated as useful tools to address the optimization of the warehousing performances and efficiency metrics. The development of such interfaces enables to test the effectiveness of the proposed hierarchical top-down procedure with huge real case studies, taken by industry applications. Whether the large part of the manuscript deals with micro concerns of warehousing nodes, also macro issues and aspects related to the planning, design, and management of the whole supply chain are enquired and discussed. The integration of macro criticalities, such as the design of the supply chain infrastructure and the placement of the logistic nodes, with micro concerns, such the design of warehousing nodes and the management of material handling, is addressed through the definition of integrated models and procedures, involving the overall supply chain and the whole product life cycle. A new integrated perspective should be applied in study and planning of global supply chains. Each aspect of the reality influences the others. Each product consumed by a customer tells a story, made by activities, transformations, handling, processes, traveling around the world. Each step of this story accounts costs, time, resources exploitation, labor, waste, pollution. The economical and environmental sustainability of the modern global supply chain is the challenge to face

A simulation approach to warehousing policies: the grandvision case

Esta tese de mestrado é um projecto desenvolvido na empresa GrandVision na área da Gestão da Cadeia de Abastecimento, mais concrectamente em Armazenagem, que apesar de muitas vezes desprezada, representa em média entre um quarto a um quinto dos custos logísticos. Apesar dos grandes avanços na tecnologia os armazéns tradicionais, de picking manual, continuam a representar 80% do universo. Aproveitando a vontade da Gestão da empresa em desenvolver projectos de melhoria para o Armazém, foi proposto o estudo ,através de simulação, de novas políticas de Armazenamento e de Picking para a operação de aprovisionamento das lojas MultiOpticas e GrandOptical. Os modelos testados em simulação partiram dos estudos previamente desenvolvidos nesta área e os resultados obtidos estão alinhados com os que foram anteriormente reportados. Com a conclusão desta tese, a Gestão da GrandVision fica no seu dispor de um procedimento de Arrumação baseado em Classes que quando combiando com uma política de Agrupamento de orderns podem trazer poupanças de tempo de ciclo a rondar os 32%, segundo o modelo de simulação.This master thesis is a project which took place in the company GrandVision. It is under the Supply Chain field of study, more precisely Warehousing; which despite having its importance underrated for many times, represents on average from one quarter to one fifth of the overall logistic costs. Regardless of the great technology break-troughs, traditional manual picker-to-part warehousing systems still represent 80% of the universe. Taking advantage of GrandVision’s management will in develop improvement projects to its warehouse; it was proposed the study, through simulation, of new Storage and Picking policies for the weekly Replenishment operation of MultiOpticas and GrandOptical Shops. The simulation models were created based on previous findings in this area of study, and results obtained are according with the ones previously reported in literature. With the conclusion of this master thesis, GrandVision’s management has in its possess a procedure of Class-Based Storage, which combined with a Batching Policy can bring, according with the simulation model, improvements around 32% of the Total Fulfillment Time

Design and optimization of an explosive storage policy in internet fulfillment warehouses

This research investigates the warehousing operations of internet retailers. The primary physical process in internet retail is fulfillment, which typically involves a large internet fulfillment warehouse (IFW) that has been built and designed exclusively for online sales and an accompanying parcel delivery network. Based on observational studies of IFW operations at a leading internet retailer, the investigations find that traditional warehousing methods are being replaced by new methods which better leverage information technology and efficiently serve the new internet retail driven supply chain economy. Traditional methods assume a warehouse moves bulk volumes to retail points where the bulks get broken down into individual items and sold. But in internet retail all the middle elements of a supply chain are combined into the IFW. Specifically, six key structural differentiations between traditional and IFW operations are identified: (i) explosive storage policy (ii) very large number of beehive storage locations (iii) bins with commingled SKUs (iv) immediate order fulfillment (v) short picking routes with single unit picks and (vi) high transaction volumes with total digital control. In combination, these have the effect of organizing the entire IFW warehouse like a forward picking area. Several models to describe and control IFW operations are developed and optimized. For IFWs the primary performance metric is order fulfillment time, the interval between order receipt and shipment, with a target of less than four hours to allow for same day shipment. Central to achieving this objective is an explosive storage policy which is defined as: An incoming bulk SKU is exploded into E storage lots such that no lot contains more than 10% of the received quantity, the lots are then stored in E locations anywhere in the warehouse without preset restrictions. The explosion ratio Ψo is introduced that measures the dispersion density, and show that in a randomized storage warehouse Ψoo\u3e0.40. Specific research objectives that are accomplished: (i) Develope a descriptive and prescriptive model for the control of IFW product flows identifying control variables and parameters and their relationship to the fulfillment time performance objective, (ii) Use a simulation analysis and baseline or greedy storage and picking algorithms to confirm that fulfillment time is a convex function of E and sensitive to Ǩ, the pick list size. For an experimental problem the fulfillment time decrease by 7% and 16% for explosion ratios ranging between Ψo=0.1 and 0.8, confirming the benefits of an explosive strategy, (iii) Develope the Bin Weighted Order Fillability (BWOF) heuristic, a fast order picking algorithm which estimates the number of pending orders than can be filled from a specific bin location. For small problems (120 orders) the BWOF performes well against an optimal assignment. For 45 test problems the BWOF matches the optimal in 28 cases and within 10% in five cases. For the large simulation experimental problems the BWOF heuristic further reduces fulfillment time by 18% for Ǩ =13, 27% for Ǩ =15 and 39% for Ǩ =17. The best fulfillment times are achieved at Ψo=0.5, allowing for additional benefits from faster storage times and reduced storage costs