scholarly journals Optimal control and simulation for production planning of network failure-prone manufacturing systems with perishable goods

2020 ◽  
Vol 146 ◽  
pp. 106614 ◽  
Author(s):  
Adel Hatami-Marbini ◽  
Seyed Mojtaba Sajadi ◽  
Hiva Malekpour

1999 ◽  
Vol 32 (2) ◽  
pp. 237-242
Author(s):  
Dong-Ping Song ◽  
Wei Xing ◽  
You-Xian Sun ◽  
Tie-Jun Wu


2019 ◽  
Vol 109 (04) ◽  
pp. 242-249
Author(s):  
A. Selmaier ◽  
T. Donhauser ◽  
T. Lechler ◽  
J. Zeitler ◽  
J. Franke

Während sich das Verhalten starr verketteter Systeme relativ einfach mittels Materialflusssimulationen modellieren lässt, sind herkömmliche Simulationsansätze für flexible Fertigungssysteme aufgrund des hohen Datenerhebungs- sowie Parametrisieraufwands nur bedingt geeignet. Jedoch kann durch das automatische Übertragen von Echtzeitdaten in das Simulationsmodell der aktuelle Zustand solcher Systeme deutlich verbessert abgebildet werden. Der Beitrag stellt ein Konzept für die simulationsgestützte Produktionsplanung schnellveränderlicher Systeme vor.   While the behaviour of rigidly linked systems is relatively easy to model by means of material flow simulation, traditional simulation approaches are only suitable to a limited extent for flexible manufacturing systems due to the high data collection and parameterization effort. However, the use of real-time data can significantly improve the simulation of such systems. This paper presents an approach for simulation-based production planning of rapidly changing systems.



Author(s):  
Andrzej Gospodarowicz ◽  
Ewa Kania ◽  
Stanislaw Krawczyk ◽  
Mieczyslaw Rymarczyk ◽  
A. Min Tjoa


1998 ◽  
Vol 08 (07) ◽  
pp. 1251-1276 ◽  
Author(s):  
SURESH P. SETHI ◽  
HANQIN ZHANG ◽  
QING ZHANG

Recently, the production control problem in stochastic manufacturing systems has generated a great deal of interest. The goal is to obtain production rates to minimize total expected surplus and production cost. This paper reviews the research devoted to minimum average cost production planning problems in stochastic manufacturing systems. Manufacturing systems involve a single or parallel failure-prone machines producing a number of different products, random production capacity, and constant demands.





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