期刊名称：JOURNAL OF OPTIMIZATION IN INDUSTRIAL ENGINEERING (JOURNAL OF INDUSTRIAL ENGINEERING)
印刷版ISSN：2251-9904
出版年度：2015
卷号：8
期号：19
页码：75-85
语种：English
出版社：ISLAMIC AZAD UNIVERSITY, QAZVIN BRANCH
摘要：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.
关键词：RELIABILITY ASSESSMENT; MARKOVIAN MODEL; NEURAL NETWORK; MONTE CARLO SIMULATION
