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Coupling of centralized and decentralized scheduling for robust production in agile production systems

Echsler Minguillon, Fabio; Lanza, Gisela 1
1 Institut für Produktionstechnik (WBK), Karlsruher Institut für Technologie (KIT)

Abstract:

Individualized products and timely delivery require agile just-in-time manufacturing operations. Scheduling needs to deliver a robust performance with high and stable results even when facing disruptions such as machine failures. Existing approaches often generate predictive schedules and adjust them reactively as disturbances occur. However, the effectiveness of rescheduling approaches highly depends on the available degrees of freedom in the predictive schedule. In the proposed approach, a centralized robust scheduling procedure is coupled with a decentralized reinforcement learning algorithm in order to adjust the required degrees of freedom for a maximally efficient production control in real-time.


Verlagsausgabe §
DOI: 10.5445/IR/1000144928
Veröffentlicht am 22.06.2022
Originalveröffentlichung
DOI: 10.1016/j.procir.2019.02.099
Scopus
Zitationen: 19
Dimensions
Zitationen: 20
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Produktionstechnik (WBK)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2019
Sprache Englisch
Identifikator ISSN: 2212-8271
KITopen-ID: 1000144928
Erschienen in Procedia CIRP
Verlag Elsevier
Band 79
Seiten 385–390
Bemerkung zur Veröffentlichung 12th CIRP Conference on Intelligent Computation in Manufacturing Engineering, 18-20 July 2018, Gulf of Naples, Italy
Vorab online veröffentlicht am 13.03.2019
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Scopus
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