Simulation-based production planning for engineer-to-order systems with random yield

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

1 Citaat (Scopus)
3 Downloads (Pure)

Samenvatting

We consider an engineer-to-order production system with unknown yield. We model the yield as a random variable which represents the percentage output obtained from one unit of production quantity. We develop a beta-regression model in which the mean value of the yield depends on the unique attributes of the engineer-to-order product. Assuming that the beta-regression parameters are unknown by the decision maker, we investigate the problem of identifying the optimal production quantity. Adopting a Bayesian approach for modeling the uncertainty in the beta-regression parameters, we use simulation to approximate the posterior distributions of these parameters. We further quantify the increase in the expected cost due to the so-called input uncertainty as a function of the size of the historical data set, the product attributes, and economic parameters. We also introduce a sampling-based algorithm that reduces the average increase in the expected cost due to input uncertainty.

Originele taal-2Engels
Titel2017 Winter Simulation Conference, WSC 2017
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's3275-3286
Aantal pagina's12
ISBN van elektronische versie9781538634288
ISBN van geprinte versie9781538634271
DOI's
StatusGepubliceerd - 4 jan 2018
Evenement2017 Winter Simulation Conference (WSC 2017) - Las Vegas, Verenigde Staten van Amerika
Duur: 3 dec 20176 dec 2017
http://meetings2.informs.org/wordpress/wsc2017/

Congres

Congres2017 Winter Simulation Conference (WSC 2017)
Verkorte titelWSC 2017
LandVerenigde Staten van Amerika
StadLas Vegas
Periode3/12/176/12/17
Internet adres

    Vingerafdruk

Citeer dit

Akcay, A., & Martagan, T. (2018). Simulation-based production planning for engineer-to-order systems with random yield. In 2017 Winter Simulation Conference, WSC 2017 (blz. 3275-3286). Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/WSC.2017.8248045