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SIMULATION MODELS COMPARISON FOR THE PRODUCTION CONTROL OF UNRELIABLE MANUFACTURING SYSTEMS

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JANUARY-DECEMBER 2014   -  Volume: 2 -  Pages: [12 p.]

DOI:

https://doi.org/10.6036/MN7262

Authors:

HECTOR RIVERA GOMEZ
-
JAIME GARNICA GONZALEZ
- OSCAR MONTAÑO ARANGO -
EVA SELENE HERNANDEZ GRESS

Disciplines:

  • Organization and management of enterprises (NIVELES ÓPTIMOS DE PRODUCCIÓN )

Downloads:   83

How to cite this paper:  
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Received Date :   4 August 2014

Reviewing Date :   27 October 2014

Accepted Date :   1 November 2014


Key words:
Metodologías de modelación, Sistemas de manufactura, Simulación discreta, Simulación continua, Control óptimo, modeling methodologies, manufacturing system, discrete simulation, continuous simulation, optimal control.
Article type:
ARTICULO DE INVESTIGACION / RESEARCH ARTICLE
Section:
RESEARCH ARTICLES

ABSTRACT:
This paper deals with the production control problem of an unreliable manufacturing system subject to random failures and repairs. The applied production policy is based on the so-called Hedging Point Policy (HPP), which consists in building and maintaining a safety stock of product in order to fulfill the demand, and protect the production system against shortages during maintenance actions. The main objective of the study is the assessment of the ARENA simulation software at reproducing accurately the dynamics and the stochastic behavior of a manufacturing system governed by the HPP. To this end, three simulation models were developed, based on concepts of discrete and continuous simulation. The HPP is applied as the control rule for the simulation models, where we seek to determine the optimal production policy that minimizes the total incurred cost which comprises the inventory and the backlog cost. Simulation results are validated with an analytical solution and a comparison of the simulation models are conducted in terms of accuracy and time economy. The obtained results show that the continuous simulation model with C++ inserts outperforms the rest of the models.

Keywords: modeling methodologies, manufacturing system, discrete simulation, continuous simulation, optimal control.

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