347 research outputs found

    Arrival first queueing networks with applications in kanban production systems

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    In this paper we introduce a new class of queueing networks called {\it arrival first networks}. We characterise its transition rates and derive the relationship between arrival rules, linear partial balance equations, and product form stationary distributions. This model is motivated by production systems operating under a kanban protocol. In contrast with the conventional {\em departure first networks}, where a transition is initiated by service completion of items at the originating nodes that are subsequently routed to the destination nodes (push system), in an arrival first network a transition is initiated by the destination nodes of the items and subsequently those items are processed at and removed from the originating nodes (pull system). These are similar to the push and pull systems in manufacturing systems

    Performance evaluation of shuttle-based storage and retrieval systems using discrete-time queueing network models

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    Shuttle-based storage and retrieval systems (SBS/RSs) are an important part of today‘s warehouses. In this work, a new approach is developed that can be applied to model different configurations of SBS/RSs. The approach is based on the modeling of SBS/RSs as discrete-time open queueing networks and yields the complete probability distributions of the performance measures

    Performance evaluation of warehouses with automated storage and retrieval technologies.

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    In this dissertation, we study the performance evaluation of two automated warehouse material handling (MH) technologies - automated storage/retrieval system (AS/RS) and autonomous vehicle storage/retrieval system (AVS/RS). AS/RS is a traditional automated warehouse MH technology and has been used for more than five decades. AVS/RS is a relatively new automated warehouse MH technology and an alternative to AS/RS. There are two possible configurations of AVS/RS: AVS/RS with tier-captive vehicles and AVS/RS with tier-to-tier vehicles. We model the AS/RS and both configurations of the AVS/RS as queueing networks. We analyze and develop approximate algorithms for these network models and use them to estimate performance of the two automated warehouse MH technologies. Chapter 2 contains two parts. The first part is a brief review of existing papers about AS/RS and AVS/RS. The second part is a methodological review of queueing network theory, which serves as a building block for our study. In Chapter 3, we model AS/RSs and AVS/RSs with tier-captive vehicles as open queueing networks (OQNs). We show how to analyze OQNs and estimate related performance measures. We then apply an existing OQN analyzer to compare the two MH technologies and answer various design questions. In Chapter 4 and Chapter 5, we present some efficient algorithms to solve SOQN. We show how to model AVS/RSs with tier-to-tier vehicles as SOQNs and evaluate performance of these designs in Chapter 6. AVS/RS is a relatively new automated warehouse design technology. Hence, there are few efficient analytical tools to evaluate performance measures of this technology. We developed some efficient algorithms based on SOQN to quickly and effectively evaluate performance of AVS/RS. Additionally, we present a tool that helps a warehouse designer during the concepting stage to determine the type of MH technology to use, analyze numerous alternate warehouse configurations and select one of these for final implementation

    Integrated Analytical Performance Evaluation Models of Warehouses

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    Warehouse design process is a complex process with numerous alternatives at all design stages, with focus on throughput capacity, inventory size and material handling equipment requirements. Enumerating all feasible solutions that satisfy the throughput and storage capacity requirements is not practical. Analytical models play a key role in the preliminary design stages in identifying several good initial warehouse configurations. This research effort pertains to the development of integrated analytical models that address capacity/congestion and inventory issues simultaneously in warehouse systems.The first part of the dissertation focuses on the development of a queueing network model of the "shared-server system," which is an inventory store with a server performing both storage and retrieval operations. First, we modeled the shared-server system using Continuous Time Markov Chains (CTMC) under exponential assumptions. We then developed an approximate queueing network model for general arrivals and general service time distribution, and designed a solution procedure based on the parametric-decomposition method. Later, we extended these models to include multi-server cases.The second part of the dissertation focuses on the development of a queueing-inventory (QI) model of an order-picking system. The configuration of the unit-load that is stored (pallets) is different from that which is retrieved (cases). We developed a single stage QI model with batch processing to represent the material movement in and out of the forward inventory store. We then extended these models to include multi-server cases.The last part of the dissertation focuses on the development of an integrated model that demonstrates the applicability of these key building blocks (the shared-server system and the order-picking system) in developing an end-to-end model of the warehouse system. Extensive numerical experiments indicate that the proposed analytical models can be solved in a computationally efficient manner and are accurate for a wide range of parameter values when compared with simulation estimates.Industrial Engineering & Managemen

    Performance analysis at the crossroad of queueing theory and road traffic

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