KIT | KIT-Bibliothek | Impressum | Datenschutz

Applying frequency based forecasting for resource allocation

May, Marvin Carl ORCID iD icon 1; Kiefer, Lars 1; Frey, Alex 1; Duffie, Neil A.; Lanza, Gisela 1
1 Institut für Produktionstechnik (WBK), Karlsruher Institut für Technologie (KIT)

Abstract:

Soaring complexity in supply chains with more fluctuations and ever increasing uncertainty in demand puts an increased focus on flexibility and changeability in manufacturing. Thus, it is increasingly important to determine the right change type, such as changes in the number of employees or overtime, at the right time in order to be able to react appropriately and sustainably to changes in demand. The developed approach uses frequency analysis to predict future changes in demand in different frequency ranges in order to assign appropriate change types to them and optimize the change intensity for each change type and time step. The foundation of the related algorithm is a discrete Fourier analysis that extracts relevant frequencies and assigns change types using generative algorithms to enable cost-minimizing production. The algorithm is validated against LSTM and ARIMA forecasting in a use case with seasonal time series including different noise levels.


Verlagsausgabe §
DOI: 10.5445/IR/1000168676
Veröffentlicht am 27.02.2024
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Produktionstechnik (WBK)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2023
Sprache Englisch
Identifikator ISSN: 2212-8271
KITopen-ID: 1000168676
Erschienen in Procedia CIRP
Verlag Elsevier
Band 120
Seiten 147 – 152
Schlagwörter Frequency, Fourier analysis, Resource allocation, LSTM, ARIMA, Generic Algorithm
Nachgewiesen in Scopus
Dimensions
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page