Two warehouse material location selection

As a company increases their use of warehouse, the excess inventory that cannot be stored in the owned warehouse are transferred to a third-party warehouse in which the company pays rent and transportation cost for storing items and moving items back to the production site. This research introduces the concept of material location selection that allocates materials to these two warehouses while minimizing the total storage and transportation costs. A two-warehouse material flow network model is formulated and then derived to generate five material location policies for evaluating the material flow situation of a real manufacturing company. The result showed that there is around 15%-40% cost saving that the company potentially obtains by systematically allocating materials to warehouses. A material location selection model is then proposed with a two-warehouse production planning model that accounts for workload dependent lead-time. In addition, an inventory rollback algorithm is given as means to bypass imperfect material movement information, in order to analyze inventory levels. Last, an application of the material location selection and production planning models is given as a potential extension of these models for determining an expansion size of the owned warehouse.Includes biblographical reference

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

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

Optimizing Multi-Item Inventory Management Decisions in Healthcare Facilities

Healthcare costs in the United States continue to grow at a significant rate. In many healthcare settings material supply and inventory management represent significant areas of opportunity for managing healthcare costs more effectively. In this dissertation, we explore three topics related to these areas. In the first chapter, we propose methodologies to help clinicians store medications and medical supplies optimally in space-constrained, decentralized Automated Dispensing Cabinets (ADCs) located on hospital patient floors. This is significant for many reasons: first, locating and storing medical supplies and pharmaceutical products within automated dispensing devices on patient floors is often not done efficiently and these devices are not utilized optimally. The primary purpose of an ADC is to ensure ready access of pharmaceuticals and medical supplies at floor locations within a hospital. However, the allocation of the limited space within an ADC to these items is typically not planned systematically and this often results in wasted staff effort as clinical personnel must expend effort in locating and retrieving them from a hospital's central pharmacy/storage location. A second major issue in using these devices is human error associated with the selection of pharmaceuticals from floor storage. These problems are addressed via two different mixed integer programming (MIP) models. In the first model, we only focus on the tradeoff between storing many of a few items and storing smaller quantities of many items and in the second model we also consider how to reduce medication dispensing errors by designing appropriate storage layouts. We also propose valid inequalities and continuous relaxations to facilitate solving instances of a scale that represents real-world applications. Based on computational tests using actual data, these refinements can reduce the run time to well under 10\% of the time of the base model and thereby allow for large, real-world instances to be readily solved. Our results indicate that using simplistic space allocation and inventory management policies, rather than our modeling approach, could result in about twice as much work for medical staff while still leaving unused space in the ADC. The second (position-based) model decreases risks associated with medication errors by at least 38\% over simpler methods. In the next chapter, we investigate a class of inventory control systems which are used in inventory management systems at points of use (POUs) in hospitals. This class of inventory control systems is characterized by stochastic demand, periodic reviews with fractional (or very small) lead time, expedited delivery when stockouts occur, limited storage capacity, and service level requirements. We develop discrete time Markov chain models of different inventory control systems that deal with all of these characteristics while minimizing the total expected replenishment effort at POUs. We have derived closed form solutions and propose an exact algorithm to calculate the limiting probability distribution by locally decomposing the state space. We investigate the structural results and based on our approach we propose an algorithm that is much easier to use in practical applications compared to solving the steady state equations in Markov models, and the computational effort required for finding the replenishment policy parameters is reduced. In the final chapter, we address the management of inventory for multiple non-perishable medical supplies in floor storage by selecting the optimal inventory policy for each item along with its corresponding operating parameters. In practice, hospitals tend to assign the same overall inventory control policy to all or the majority of the items. This simplistic approach often leads to wasted staff effort and ineffective policies. The objective of our research is to minimize the average labor effort required to count and replenish all of the items, while providing an acceptably high level of service (avoiding stock outs) and taking into account constraints on available space. We consider four policies: PAR, $(R,s,S)$, $(R,s,Q)$, and a two-bin Kanban system. We illustrate the model with actual data from a healthcare setting and propose some practical insights and guidelines on how to choose a hybrid inventory system based on demand and system characteristics

Analisi e confronto di diverse strategie di supply network design per l'e-grocery

L'e-commerce è un canale di vendita sempre più diffuso in tutto il mercato mondiale. Di recente anche il mercato alimentare si è interessato all'espansione di questo fenomeno, soprattutto durante l'emergenza pandemica da COVID-19, quando la spesa in e-grocery è notevolmente aumentata. Inoltre è rimasto un canale di vendita diffuso anche successivamente, nello stato non emergenziale. Per soddisfare questa specifica domanda di mercato, le catene di supermercati si trovano ad affrontare la necessità di un re-design con una nuova prospettiva logistica. Un negoziante può adempiere ad ordini online in diversi modi; può elaborarli direttamente nei negozi utilizzando il personale per fare la spesa dagli scaffali durante le ore non di punta. In alternativa, alcuni negozi minori possono essere chiusi alla clientela e dedicati all'evasione degli ordini online (negozi scuri). Un'altra strategia consiste nell'effettuare ordini online da un unico centro di distribuzione (e-hub). Infine, gli ordini online possono essere completamente gestiti da multi e-hub. Questo lavoro illustra alcune strategie per adempiere a tali esigenze