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Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):

A. Schmid, F. Kamhuber, T. Sobottka, W. Sihn:
"DISPO 4.0 | Simulation-Based Optimization of Stochastic Demand Calculation in Consumption-Based Material Planning in the Capital Goods Industry";
Vortrag: MOTSP 2022 - 14th Intern. Scientific Conference Mangement of Technology - Step to SustainableProduction, Primosten/Dalmatia, Croatia; 08.06.2022 - 10.06.2022; in: "Tehnički Glasnik", (2022), ISSN: 1848-5588.



Kurzfassung englisch:
This paper presents a digital material planning approach, utilizing simulation-based optimization to select and parametrize article specific demand forecasting methods.
Demand forecasts are the basis of material requirements planning in consumption-based material planning, and are an essential lever for efficient inventory and order calculation. Despite their acknowledged potential, digital tools for optimized demand calculation are still lacking in practice. Thus, the goal of the presented approach to provide an application-oriented method to optimally select and parametrize state-of-the-art forecasting methods, based on product-specific demand data. In this approach, a rule-based selection heuristic is combined with static simulation of demand time-series and a metaheuristics-based optimization of forecasting parameters, to provide automatically optimized article-specific demand forecasts. Case studies for two companies in the capital goods industry evaluate and quantify the application potential. The results point to significantly improved, item-specific demand planning.

Schlagworte:
demand planning, exponential smoothing, forecasting, parameter optimization, simulation


"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.31803/tg-20220504151004


Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.