A discrete event simulation based production line optimization through Markov decision process

Feng, Y; Fan, W; Qin, Y

A discrete event simulation based production line optimization through Markov decision process

Feng, Y

Fan, W Qin, Y

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Publication Type:: Conference Proceeding
Citation:: Communications in Computer and Information Science, 2013, 402 pp. 385 - 390
Issue Date:: 2013-01-01

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Field	Value	Language
dc.contributor.author	Feng, Y https://orcid.org/0000-0002-3097-3896	en_US
dc.contributor.author	Fan, W	en_US
dc.contributor.author	Qin, Y	en_US
dc.date.issued	2013-01-01	en_US
dc.identifier.citation	Communications in Computer and Information Science, 2013, 402 pp. 385 - 390	en_US
dc.identifier.isbn	9783642450365	en_US
dc.identifier.issn	1865-0929	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121059
dc.description.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. © Springer-Verlag Berlin Heidelberg 2013.	en_US
dc.relation.ispartof	Communications in Computer and Information Science	en_US
dc.relation.isbasedon	10.1007/978-3-642-45037-2_39	en_US
dc.title	A discrete event simulation based production line optimization through Markov decision process	en_US
dc.type	Conference Proceeding
utslib.citation.volume	402	en_US
utslib.for	080503 Networking and Communications	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - QSI - Centre for Quantum Software and Information
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	402	en_US

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. © Springer-Verlag Berlin Heidelberg 2013.

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http://hdl.handle.net/10453/121059