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A Discrete Event Simulation Based Production Line Optimization through Markov Decision Process

  • Yuan Feng
  • Wenhui Fan
  • Yuanhui Qin
Part of the Communications in Computer and Information Science book series (CCIS, volume 402)

Abstract

In this paper, we built simulation model of the production line from one car engine parts plant in Beijing, in order to find proper solutions to raise productivity. The method of Discrete Event Simulation was used to construct the simulation model on account of the fact that production line was a typical discrete event system. Besides, worker heterogeneity, stochastic environment and the effect of worker learning and forgetting were introduced into simulation model to make it closer to reality. We proposed different schedule policies to manage the running of production line with the verification from simulation experiments. Then, by taking advantage of the simulation results obtained previous, we built the optimization model by applying Markov Decision Process (MDP) to seek for the best policy promoting the productivity of production line.

Keywords

discrete event simulation production line learning and forgetting markov decision process 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yuan Feng
    • 1
  • Wenhui Fan
    • 1
  • Yuanhui Qin
    • 2
  1. 1.State CIMS Engineering Research Center, Department of AutomationTsinghua UniversityBeijingP.R. China
  2. 2.System Engineering Research InstituteBeijingP.R. China

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