Monte Carlo Simulation to Compare Markovian and Neural Network Models for Reliability Assessment in Multiple AGV Manufacturing System

Journal of Optimization in Industrial Engineering

مقاله 7، دوره 9، شماره 19، خرداد 2016، صفحه 75-86   

نوع مقاله: Original Manuscript

شناسه دیجیتال (DOI): 10.22094/joie.2016.190

نویسندگان

Hamed Fazlollahtabar^* ؛ Mohamma Saidi-Mehrabad

Iran University of Science and Technology

چکیده

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, therefore 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.
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, therefore a Markovian model is proposed for reliability assessment.

کلیدواژه‌ها

Reliability assessment؛ Markovian model؛ Neural Network؛ Monte Carlo simulation