Thesis (M.S.)--Ohio University, August, 2004. / Title from PDF t.p. Includes bibliographical references (p. 120-125)

This research investigates analytical models that might serve to support decisions in the early stages of designing high volume small parts order picking systems. Because the development of analytical closed-forms is challenging, a common approach is to use simulation models for detailed design performance assessment. However, simulation is not suitable for early stage design purposes; because simulation models are time-consuming (thus expensive) to construct and execute, especially when the number of alternatives to evaluate is large. If available, analytical models are computationally cheaper. They provide faster and more flexible solutions and though usually less detailed, may be adequate to support early stages of design. The challenge is to develop generic analytic models providing useful results for a class of problems. This research focuses on a class of problems in high volume small parts order picking systems with pick-to-buffer technology. This is a new technology, and not yet in widespread use. The novelty in the modeling approach is the distinct separation of item-picking and order assembly operations which permits the development of performance models for both throughput and service level. Essentially the system is modeled as a tandem queue, and the two detailed models for the picking and assembly subsystems are developed based on detailed description of the operations. Solving the model provides estimates for performance measures, such as order cycle time and system throughput, which are essential in design. The approximation method requires estimating the squared coefficient of interdeparture times from the classical GX/G/1 queuing model, and a suitable approximation is derived in this thesis. Computational tests show the model to provide reasonably accurate estimates of system performance, with minimal computational overhead. To support the proposed queuing model, new models are developed for estimating mean and squared coefficient of variation for pick and assembly operation times. These models include the variability of order contents and the picking process, along with the physical layout. Results of the estimation compare very well with that of simulation.

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The need to be economically successful is the key driver for companies to be innovative and implement new technologies with increasing efficiency and effectiveness. Uncertainty about whether to use new technologies and missing knowledge about their advantages lead to staggering and withholding from fast diffusion of innovations. Focusing on the industry of logistics and the technology Mixed Reality, this research project developed a methodical approach for evaluating the fitness of an innovative technology and a specific process of application. A mixed methods approach was derived, based on interviews and experiments. The main methodologies used, were semi-structured interviews with decision makers in logistics companies to elaborate triggering criteria in the investment process and laboratory experiments for the evaluation of competing technologies. These methods were framed by an initial field experiment and feedback interviews after the analysis for the validation of the approach. The research proved the competitively viable applicability of Mixed Reality and its specific strengths and weaknesses in manual order picking. This set the foundation for possible further development and implementation of the technology. The developed methodological approach proved to be a valid and reliable assessment of the intersection between a technology and specified process of application. This can greatly enhance the speed of implementing new innovations and gaining competitive advantages for companies.

The area of order picking has been widely studied but still there is no general approach covering all the potential variables of a unique case. Optimizing the product placement is a useful way to improve order picking through reduced travel distances and goes hand in hand with an appropriate batching strategy and routing policy. The existing methods are of mathematical basis and can be costly to implement and it is therefore necessary to develop a non-mathematical approach that can be used for distribution centers and in this particular case, the warehouse of a mail order company. Literature is reviewed to investigate the current situation of a large Swedish mail order retailer for the development of a unique product assignment strategy, taking into consideration potential variables. It was found out that a lot of trade-offs are being done all the time between travel distances of the SKUs. Also, it was found out that “cart blocking” might be a potential problem when using a turnover-based storage assignment strategy.

Logistics makes extensive use of human and material resources to achieve a target level of customer service at the lowest possible cost. It has been recognized as a major key to success in commerce and industry, and continues to evolve radically and grow in importance in recent years. Warehousing, as one of the most costly elements of logistics, is often the central operation in most logistics networks. Its successful management is critical in terms of both cost and service. In this thesis, two problem areas in warehouse logistics are studied: stock loading and order picking. Stock loading is an essential operation in modern logistics. Improvement on container capacity utilization and loading efficiency significantly reduces costs. For a given set of boxes in different sizes and an unlimited number of identical containers, the basic cargo loading problem is to determine the minimum number of containers required. The problem is proven NP-hard. To tackle this problem, a Tabu search optimization with a tree-based cargo loading algorithm as its inner heuristic is proposed. This approach has flexibility in taking different box conditions into consideration, and can find better solutions on average than other recent meta- or heuristic algorithms. Decreasing order sizes and increasing fuel costs provide a strong incentive for the inner-city truck loading operation to utilize container space more efficiently in transporting goods to multiple clients during one trip. This considers not only traditional loading constraints, but also multi-drop requirements. A wallbuilding heuristics based on a binary tree data structure is proposed to handle these side constraints. A dynamic space decomposition approach, together with a repacking and space amalgamation strategy, permits an efficient and effective loading plan. Order picking, one of the most critical warehousing operations, is the second problem studied in this thesis. An analytical approximation model is proposed based on probability modeling and queueing network theory applied to a synchronized zone picker-to-part order picking system with different routing and ABC-class inventory storage policies. The numerical results are compared and validated via simulation. The resulting model can therefore be usefully applied in the design and selection process of order picking systems. The routing versus storage issues are further investigated with a simulation model. This extends the existing research by evaluating multiple routing and storage policies under varying operating conditions. Results show that the midpoint, return and traversal routing policies generally perform best when paired with perimeter, across-aisle and within-aisle storage strategies, respectively. Yet performance is indeed dependent on demand patterns, zone sizes, batch sizes and order sizes. At first glance, order picking and stock loading operation seem to pursue different objectives. However, they are two related operations conducted sequentially from internal to the outbound side of warehousing. An efficient order picking system is a precondition for an effective loading operation at the shipping dock, especially when multiple orders need to be selected for consolidation in shipment. The proposed loading algorithms and the order picking system performance evaluation models can be used to further study the effective integration of these two functions. / published_or_final_version / Mathematics / Doctoral / Doctor of Philosophy

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Thesis (M.S.)--Ohio University, November, 2002. / Title from PDF t.p.

Stadium driver i dagsläget en centrallagerlösning i Norrköping sedan år 2006. Det har skett en stabil ökning av både butiker samt omsättning sedan bolaget startades. Stadium har ett avtal med PostNord angående driften av lagerverksamheten på centrallagret samt Pema angående bemanningen. Bolagets ökning av butiker har lett till att de nått en väldigt hög nivå i beläggning i centrallagret och därför behövdes en genomlysning av centrallagrets plockprocesser ske. Ett beslutsunderlag har tagits fram för att hjälpa Stadiumlagret med sin frekvensläggning av orderplocket. Två olika plockprocesser har jämförts med varandra, Banan och ett plocktorg. Banan är en automatiserad bana där plocklådor med ordrar transporteras längs Banans olika plockzoner, medan plocktorget är en tom yta där pallar med artiklar placeras och sedan plockas. Tidsstudier och observationer genomfördes på både Banan och plocktorget och dess olika steg i processerna, för att se vilken som var mest tidseffektiv. Kriterier och variabler togs fram för att kunna avgöra vad det är som påverkar respektive plockprocess. Beräkningar utformades för att göra Banans och plocktorgets tider jämförbara. Den plockprocess som sedan tog minst tid totalt skulle vara den bästa plockprocessen att plocka i. För att utforma ett beslutsunderlag som enkelt skulle illustrera ifall skor skulle plockas på plocktorget eller Banan, gjorde valet att utforma beslutsunderlaget i en matris. I matrisen illustreras vid vilket antal artiklar en brytpunkt finns där det skulle vara bättre att plocka på plocktorg. För att undersöka ifall centrallagret någon gång kom upp i de kvantiteter som krävdes för att nå brytpunkten användes verkliga exempel. En känslighetsanalys genomfördes där data från verkliga exempel användes och sorterades på olika sätt, för att undersöka om stora skillnader i resultatet i matrisen skulle uppenbaras. Det resulterade i sex olika matriser, tre olika sorteringar för två separata dagar av orderplock. Beslutsunderlagets matris visade att Banan var den mest effektiva plockprocessen att använda i den dagliga verksamheten för orderplocket. Anledningen till det var att Stadiumlagret inte plockade skor i de kvantiteter som brytpunkterna efterfrågade. Oavsett hur datan sorteras så övergick aldrig den totala kvantiteten av orderplock de brytpunkterna som hade beräknats. Det var en av sorteringarna som kom närmre brytpunkten än de andra två, men inte tillräckligt nära för att frekvenslägga orderplocket på plocktroget istället för Banan. Rekommendationen till PostNord blev därför att de inte skulle använda plocktorget till det ordinarie orderplocket i den dagliga verksamheten, på grund av att det är mindre effektivt att plocka på plocktorget. Plocktorget kan dock användas som ett komplement till Banan precis som den används i dagsläget. Tillfällen då plocktorget kan användas är när det exempelvis inte finns tillräckligt antal lediga plockplatser på Banan, om artiklarna är för otympliga för att plocka på Banan eller om antalet pieces av en artikel skulle medföra orimligt många påfyllningar av Banans plockplatser.