4,007 research outputs found

    Integer linear programming formulation of the vehicle positioning problem in automated manufacturing systems

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    8 pĂĄginasThis paper addresses the problem of vehicle location (positioning) for automated transport in fully automated manufacturing systems. This study is motivated by the complexity of vehicle control found in modern integrated circuit semiconductor fabrication facilities where the material handling network path is composed of multiple loops interconnected. In order to contribute to decrease the manufacturing lead-time of semiconductor products, we propose an integer linear program that minimizes the maximum time needed to serve a transport request. Computation experiments are based on real-life data. We discuss the practical usefulness of the mathematical model by means of a simulation experiment used to analyze the factory operational behavio

    A Review Of Design And Control Of Automated Guided Vehicle Systems

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    This paper presents a review on design and control of automated guided vehicle systems. We address most key related issues including guide-path design, estimating the number of vehicles, vehicle scheduling, idle-vehicle positioning, battery management, vehicle routing, and conflict resolution. We discuss and classify important models and results from key publications in literature on automated guided vehicle systems, including often-neglected areas, such as idle-vehicle positioning and battery management. In addition, we propose a decision framework for design and implementation of automated guided vehicle systems, and suggest some fruitful research directions

    Multi-agent path planning for mobile robots with discrete-step locomotion

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    The \u201cswing-and-dock\u201d (SaD) model for realizing displacements has been invented for and is used by the mobile robotic fixtures developed in the SwarmItFix European project. This form of locomotion can be a valuable capability for material handling agents, and fixturing agents enabling simultaneous handling in a non-linear fashion and increasing manufacturing flexibility. The thesis focuses on the design of SaD path planning algorithms for the motion of the agent

    Automated guided conveyor (AGC)

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    This project is focused on development of the control system for Automated Guided Conveyor (AGC) by using PIC 18F4550. Two approaches are proposed for this project; hardware approach where involves the development and design of AGC prototype, line follower, sensor circuit and controller circuit and software approach when the system of AGC are write by using microcode studio programmed. This project concentrates on developing the automatic system for AGC which about how the AGC will operate, involve of the movement mechanism. This prototype takes into account when AGC travel and also tries to travel in order by following the line follower. This thesis also includes the test automatic system involving test program and test circuit for the AGC before proceed to the prototype AGC control system

    The relevance of outsourcing and leagile strategies in performance optimization of an integrated process planning and scheduling

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    Over the past few years growing global competition has forced the manufacturing industries to upgrade their old production strategies with the modern day approaches. As a result, recent interest has been developed towards finding an appropriate policy that could enable them to compete with others, and facilitate them to emerge as a market winner. Keeping in mind the abovementioned facts, in this paper the authors have proposed an integrated process planning and scheduling model inheriting the salient features of outsourcing, and leagile principles to compete in the existing market scenario. The paper also proposes a model based on leagile principles, where the integrated planning management has been practiced. In the present work a scheduling problem has been considered and overall minimization of makespan has been aimed. The paper shows the relevance of both the strategies in performance enhancement of the industries, in terms of their reduced makespan. The authors have also proposed a new hybrid Enhanced Swift Converging Simulated Annealing (ESCSA) algorithm, to solve the complex real-time scheduling problems. The proposed algorithm inherits the prominent features of the Genetic Algorithm (GA), Simulated Annealing (SA), and the Fuzzy Logic Controller (FLC). The ESCSA algorithm reduces the makespan significantly in less computational time and number of iterations. The efficacy of the proposed algorithm has been shown by comparing the results with GA, SA, Tabu, and hybrid Tabu-SA optimization methods

    Sea Container Terminals

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    Due to a rapid growth in world trade and a huge increase in containerized goods, sea container terminals play a vital role in globe-spanning supply chains. Container terminals should be able to handle large ships, with large call sizes within the shortest time possible, and at competitive rates. In response, terminal operators, shipping liners, and port authorities are investing in new technologies to improve container handling infrastructure and operational efficiency. Container terminals face challenging research problems which have received much attention from the academic community. The focus of this paper is to highlight the recent developments in the container terminals, which can be categorized into three areas: (1) innovative container terminal technologies, (2) new OR directions and models for existing research areas, and (3) emerging areas in container terminal research. By choosing this focus, we complement existing reviews on container terminal operations

    Development of deterministic collision-avoidance algorithms for routing automated guided vehicles

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    A manufacturing job spends a small portion of its total flow time being processed on machines, and during the remaining time, either it is in a queue or being transported from one work center to another. In a fully automated material-handling environment, automated guided vehicles (AGV) perform the function of transporting the jobs between workstations, and high operational costs are involved in these material-handling activities. Consequently, the AGV route schedule dictates subsequent work-center scheduling. For an AGV job transportation schedule to be effective, the issue of collisions amongst AGV during travel needs to be addressed. Such collisions cause stalemate situations that potentially disrupt the flow of materials in the job shop, adding to the non-value time of job processing, and thus, increase the material handling and inventory holding costs. The current research goal was to develop a methodology that could effectively and efficiently derive optimal AGV routes for a given set of transportation requests, considering the issue of collisions amongst AGV during travel. As part of the solution approach in the proposed work, an integer linear program was formulated in Phase I with the capability of optimally predicting the AGV routes for a deterministic set of transportation requests. Collision avoidance constraints were developed in this model. The model was programmed using OPL / Visual Basic, and the program feasibility were experimentally analyzed for different problem domain specifications. Due to the complexity and combinatorial nature of the formulation in Phase I, computationally it was expected to be NP-Hard. Hence, to improve the computation prediction capability (estimation of upper bounds), it was required that in Phase II, heuristics be developed to relax the computational complexity of the original problem. In Phase III, experimental techniques were used to compute the lower and upper bounds of the original problem. The performances of the different heuristics were compared using experimental analysis

    Design and Control of Warehouse Order Picking: a literature review

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    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

    Cross-docking: A systematic literature review

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    This paper identifies the major research concepts, techniques, and models covered in the cross-docking literature. A systematic literature review is conducted using the BibExcel bibliometric analysis and Gephi network analysis tools. A research focus parallelship network (RFPN) analysis and keyword co-occurrence network (KCON) analysis are used to identify the primary research themes. The RFPN results suggest that vehicle routing, inventory control, scheduling, warehousing, and distribution are most studied. Of the optimization and simulation techniques applied in cross-docking, linear and integer programming has received much attention. The paper informs researchers interested in investigating cross-docking through an integrated perspective of the research gaps in this domain. This paper systematically reviews the literature on cross-docking, identifies the major research areas, and provides a survey of the techniques and models adopted by researchers in the areas related to cross-docking
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