36 research outputs found

    Simulation Study of a Semi-Dynamic AGV-Container Unit Job Deployment Scheme

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    Automated Guided Vehicle (AGV) Container-Job deployment is essentially a vehicle-dispatching problem. In this problem, the impact of vehicle dispatching polices on the ship makespan for discharging and/or loading operations is analyzed. In particular, given a storage location for each container to be discharged from the ship and given the current location of each container to be loaded onto the ship, the problem is to propose an efficient deployment scheme to dispatch vehicles to containers so as to minimize the makespan of the ship so as to increase the throughput. The makespan of the ship refers to the time a ship spends at the port for loading and unloading operations. In this paper, we will compare the performance of current deployment scheme used with the new proposed deployment scheme, both with deadlock prediction & avoidance algorithm done in previous study [1]. The prediction & avoidance algorithm predicts and avoids cyclic deadlock. The current deployment scheme, namely pmds makes use of a greedy heuristics which dispatches the available vehicle that will reach the quay with the minimum amount of time the vehicle has to spend waiting for the crane to discharge/load the container from/onto the ship. The new deployment scheme, namely mcf aims to formulate the problem as a minimum cost flow problem, which will then be solved by network simplex code. The two simulation models are implemented using discrete-event simulation software, AutoMod, and the performances of both deployment schemes are analyzed. The simulation results show that the new deployment scheme will result in a higher throughput and lower ship makespan than the current deployment scheme.Singapore-MIT Alliance (SMA

    Determining The Optimal Order Picking Batch Size In Single Aisle Warehouses

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    This work aims at investigating the influence of picking batch size to average time in system of orders in a one-aisle warehouse under the assumption that order arrivals follow a Poisson process and items are uniformly distributed over the aisle's length. We model this problem as an M/G[k]/1 queue in which orders are served in batches of exactly orders. The average time in system of the M/G[k]/1 queue is difficult to obtain for general service times. To circumvent this obstacle, we perform an extensive numerical experiment on the average time in system of the model when the service time is deterministic (M/D[k]/1) or exponentially distributed (M/M[k]/1). These results are then compared with the corresponding times in system of the actual model taken from simulation runs. A variance analysis is carried out and its result elicits that the M/D/[k]/1 queue is a very good approximation for the average time in system of orders. Correspondingly, the optimal picking batch size of the real system ca

    Methodology to develop hybrid simulation/emulation model.

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    Trends towards reduced life-time of products and globalised competition has increased pressure on manufacturing industries to be more responsive to changing needs of product markets. Consequently, the use of simulation to describe short term future performance of manufacturing system has become more significant than ever. An application of simulation that has attracted attention is for testing of control logic before commissioning on site by using a detailed simulation model called emulation model. However, though the success of using emulation particularly in improving cost-effectiveness of automated material handling system delivery has been acknowledged by industries and simulation model developers, the uptake for this technology is still low. The major inhibitors are the high costs of its model building as well as simulation and emulation models are perceived to be non convertible.The main objective, of this research is to establish a methodology to develop simulation model that can be converted into emulation model with ease, thus making emulation technology more affordable. The product of this research called the methodology to build Hybrid Simulation Emulation Model (HSEM) is a new approach of building emulation model comprising of three phases namely (1) development of base simulation model, (2) development of detail emulation model, and (3) integration of controller with the emulation model. Important requirements for HSEM are flexibility of adding details to the simulation model and inter process communication between model and real control system. To facilitate implementation of the methodology, it is essential that the simulation software package provide functionalities for modular model development, access and adding of codes, integration with other application and real time (RT) modelling.The methodology developed offers a more affordable emulation modelling and an opening for further research into the comprehensive support for the implementation of real time control system testing using emulation

    The VR Factory : discrete event simulation implemented in a virtual environment

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    http://www.worldcat.org/oclc/3970218

    Intelligent Simulation Modeling of a Flexible Manufacturing System with Automated Guided Vehicles

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    Although simulation is a very flexible and cost effective problem solving technique, it has been traditionally limited to building models which are merely descriptive of the system under study. Relatively new approaches combine improvement heuristics and artificial intelligence with simulation to provide prescriptive power in simulation modeling. This study demonstrates the synergy obtained by bringing together the "learning automata theory" and simulation analysis. Intelligent objects are embedded in the simulation model of a Flexible Manufacturing System (FMS), in which Automated Guided Vehicles (AGVs) serve as the material handling system between four unique workcenters. The objective of the study is to find satisfactory AGV routing patterns along available paths to minimize the mean time spent by different kinds of parts in the system. System parameters such as different part routing and processing time requirements, arrivals distribution, number of palettes, available paths between workcenters, number and speed of AGVs can be defined by the user. The network of learning automata acts as the decision maker driving the simulation, and the FMS model acts as the training environment for the automata network; providing realistic, yet cost-effective and risk-free feedback. Object oriented design and implementation of the simulation model with a process oriented world view, graphical animation and visually interactive simulation (using GUI objects such as windows, menus, dialog boxes; mouse sensitive dynamic automaton trace charts and dynamic graphical statistical monitoring) are other issues dealt with in the study

    Modular development of manufacturing simulation models.

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    It is common practice within manufacturing companies to create simulation models at different time periods. These models are often used to represent various parts of the manufacturing systems. In general, these pre-built simulation models are required to be integrated together in order to evaluate the entire manufacturing system, this is not a simple task. This research addresses the issues involved in the integration of pre-built simulation models. An in depth literature review was carried out to identify current strategies to overcome these issues. Based on structured research work, a set of recommendations is proposed to ensure easy integration of models. This set of recommendations will help simulation practitioners to minimise the errors occurred during the integration of simulation models. The findings conclude more effort is required than is anticipated by most model builders and involves far more than 'just simply changing' the name of variables. A set of recommendations is therefore proposed to cope with the complexity and understanding of manufacturing systems. The research focuses on manufacturing systems but in general can be applied elsewhere

    Integrated Real-Virtuality System and Environments for Advanced Control System Developers and Machines Builders

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    The pace of technological change is increasing and sophisticated customer driven markets are forcing rapid machine evolution, increasing complexity and quality, and faster response. To survive and thrive in these markets, machine builders/suppliers require absolute customer and market orientation, focusing on .. rapid provision of solutions rather than products. Their production systems will need to accommodate unpredictable changes while maintaining financial and operational efficiency with short lead and delivery times. Real-Virtuality (R-V) systems are an innovative environment to address these requirements by facilitating enhanced support in machine system design utilising integrated real-virtual environments centred on concurrent machine system development and realization. This environment supports not only machine system design but also the development of the' control system at the same time. Utilising the Real-Virtual Mapping Environment (RVMI;:), 3-D simulation machine models can perform actual machine operations in real-time when coupled with the real machine controller. This provides a more understandable, reliable and transparent machine function and performance. The research study explores different types of controller verification methods and proposes a new method which employs the use of a control signal emulator. The research study has fomulated a novel technique for emulating quadrature encoder signals to provide virtual closed loop control of servomotors. The deployment of a control signal emulator technique makes the system unique and removes its dependency on specific hardware. Enabling the real-time data from the signal emulation environment eases the task of realising a real-time machine simulator. To evaluate the proposed architecture, three case studies were performed. The results have shown that it is possible to create verified and validated machine control programs with no modification needed when applied to the real machine. The migration from the virtual to the real world is totally seamless. The result from the ????study show that the virtual machine is able to operate and respond as a real machine in real-time. This opens up the unexplored potential of integrated 3-D virtual technology. The real-time 3-D simulation virtual machine will enable commissioning and training to be conducted '!-t an earlier stage in the design process (without having to wait for the real machine to be built). Furthermore, various test scenarios can also be developed and tested on the system which helps to provide a better lofriderstanding of the machine behaviours and responses. This research study has made an original contribution in the field of machine system development. It has contributed a novel approach of using emulated control signals to provide machine control programmers with a platform to test their application programs at machine level which involves both discrete digital signals and continuous signals. The real-time virtual environment extends the application domain for the use of simulation. The architecture proposed is generic; to be exact it is not constrained to a specific industrial control system or to a specific simulation vendor

    Modular development of manufacturing simulation models.

    Get PDF
    It is common practice within manufacturing companies to create simulation models at different time periods. These models are often used to represent various parts of the manufacturing systems. In general, these pre-built simulation models are required to be integrated together in order to evaluate the entire manufacturing system, this is not a simple task. This research addresses the issues involved in the integration of pre-built simulation models. An in depth literature review was carried out to identify current strategies to overcome these issues. Based on structured research work, a set of recommendations is proposed to ensure easy integration of models. This set of recommendations will help simulation practitioners to minimise the errors occurred during the integration of simulation models. The findings conclude more effort is required than is anticipated by most model builders and involves far more than 'just simply changing' the name of variables. A set of recommendations is therefore proposed to cope with the complexity and understanding of manufacturing systems. The research focuses on manufacturing systems but in general can be applied elsewhere
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