![Institutional Repository [SANDBOX]](images/dias.logo.png "Institutional Repository [SANDBOX]"){kind=logo}
Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
|
EL
| URI | http://purl.tuc.gr/dl/dias/07DA68CE-C4A9-4B36-9849-C21A1C39F895 | - |
| Identifier | https://ieeexplore.ieee.org/document/7844395/ | - |
| Identifier | https://doi.org/10.1109/SMC.2016.7844395 | - |
| Language | en | - |
| Extent | 6 pages | en |
| Title | A petri net based methodology for modelling, analysis, demand forecast and optimal planning of batch production systems | en |
| Creator | Vrontakis Konstantinos | en |
| Creator | Βροντακης Κωνσταντινος | el |
| Creator | Kampianakis Andreas | en |
| Creator | Καμπιανακης Ανδρεας | el |
| Creator | Tsinarakis Georgios | en |
| Creator | Τσιναρακης Γεωργιος | el |
| Publisher | Institute of Electrical and Electronics Engineers | en |
| Content Summary | A methodology for optimal production planning of an industry, processing multiple raw material types, is presented. Petri net modeling of production procedures, combined with stochastic forecast of upcoming demand, produce necessary input for a Mixed Integer Linear Problem (MILP) that calculates optimal production timeline according to various constraints. The methodology is developed for batch production systems with resource sharing between different types of final products, and is applied to a real case study system. | en |
| Type of Item | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Type of Item | Conference Full Paper | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2018-05-29 | - |
| Date of Publication | 2017 | - |
| Subject | Petri nets | en |
| Subject | Stochastic processes | en |
| Subject | Batch production systems | en |
| Subject | Demand forecasting | en |
| Subject | Integer programming | en |
| Subject | Linear programming | en |
| Bibliographic Citation | K. E. Vrontakis, A. N. Kampianakis and G. J. Tsinarakis, "A petri net based methodology for modelling, analysis, demand forecast and optimal planning of batch production systems," in 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2017, pp. 1136-1141. doi: 10.1109/SMC.2016.7844395 | en |
Copyright © DIAS 2013
