Modeling automotive assembly lines with generalized stochastic petri nets and markov decision processes with imprecise probabilities

Monica Goes Eboli, Fabio Gagliardi Cozman

Research output: Contribution to conferenceConference Paper

Abstract

This paper proposes a methodology for automotive manufacturing lines scheduling. This methodology is based on generalized stochastic Petri Nets and Markov decision processes with imprecise probabilities. The usual generalized stochastic Petri Nets is extended by allowing imprecision about probabilities to be explicitly represented and by human task time graph of different products to be attached. Once the system is modeled using this tool and its extensions, we translate the resulting models into Markov decision processes with imprecise probabilities, in order to compute optimal policies that will result in the line scheduling. This paper introduces an algorithm that performs this translation. Copyright © 2008 SAE International.
Original languageAmerican English
DOIs
StatePublished - 1 Jan 2008
Externally publishedYes
EventSAE Technical Papers -
Duration: 1 Jan 2008 → …

Conference

ConferenceSAE Technical Papers
Period1/01/08 → …

Fingerprint

Dive into the research topics of 'Modeling automotive assembly lines with generalized stochastic petri nets and markov decision processes with imprecise probabilities'. Together they form a unique fingerprint.

Cite this