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Monte Carlo Simulation to Compare Markovian and Neural Network Models for Reliability Assessment in Multiple AGV Manufacturing System
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نویسنده
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saidi-mehrabad mohammad ,fazlollahtabar hamed
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منبع
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journal of optimization in industrial engineering - 2016 - دوره : 9 - شماره : 19 - صفحه:75 -85
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چکیده
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We compare two approaches for a markovian model in flexible manufacturing systems (fmss) using monte carlo simulation. the model, which is a development of fazlollahtabar and saidi-mehrabad (2013), considers two features of automated flexible manufacturing systems equipped with automated guided vehicle (agv), namely, the reliability of machines and the reliability of agvs in a multiple agv jobshop manufacturing system. the current methods for modeling reliability of a system involve determination of system state probabilities and transition states. since the failure of the machines and agvs could be considered in different states, a markovian model is proposed for reliability assessment. the traditional markovian computation is compared with a neural network methodology. monte carlo simulation has verified the neural network method having better performance for markovian computations.
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کلیدواژه
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Reliability assessment ,Markovian model ,Neural network ,Monte Carlo simulation
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آدرس
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islamic azad university, qazvin branch, faculty of industrial & mechanical engineering, ایران, iran university of science and technology, faculty of industrial engineering, ایران
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Authors
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