Tehnički glasnik, Vol. 20 No. 4, 2026.
Prethodno priopćenje
https://doi.org/10.31803/tg-20250522101813
DISPO 4.0 | Simulation-Based Optimization of Stochastic Demand Forecast of Intermittent Material in the Capital Goods Industry
Alexander Schmid
; FHWien der WKW, University of Applied Sciences for Management & Communication, Währinger Gürtel 97, 1180 Vienna, Austria
*
Marcel Peralt Bonell
; Vienna University of Technology, Karlsplatz 13, 1040 Vienna, Austria
Felix Kamhuber
; Fraunhofer Austria Research GmbH, Theresianumgasse 7, 1040 Vienna, Austria
Sebastian Schlund
; Fraunhofer Austria Research GmbH, Theresianumgasse 7, 1040 Vienna, Austria
* Dopisni autor.
Sažetak
This research introduces a digital planning method tailored to intermittent demand, leveraging simulation-based optimization to select and parameterize forecasting techniques for individual items. Accurate demand forecasting is crucial for optimizing inventory and order quantities, especially in spare parts planning, where demand is often intermittent. Despite the recognized value of digital solutions in this area, practical implementation of optimized forecasting tools for intermittent demands remains limited. To address this gap, the proposed approach offers a practical methodology for systematically selecting and configuring forecasting techniques specifically suited to irregular demand patterns. The method combines a rule-based heuristic with a static simulation of demand time series and metaheuristic-based optimization to calibrate forecasting parameters. The outcome is an automated, item-specific forecast tailored to the characteristics of intermittent demand. The approach is validated through two practical case studies from the capital goods sector, demonstrating its effectiveness in enhancing forecast accuracy and improving intermittent item planning.
Ključne riječi
Croston’s method; demand planning; forecasting methods; intermittent demand; parameter optimization; spare parts
Hrčak ID:
351738
URI
Datum izdavanja:
15.12.2026.
Posjeta: 0 *