Influence of Forecast Error and Forecast Bias on Safety Stock on a MRP System with Rolling Horizon Forecast Updates

Wolfgang Seiringer (), Fabian Brockmann (), Klaus Altendorfer () and Thomas Felberbauer ()
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Wolfgang Seiringer: University of Applied Sciences Upper Austria
Fabian Brockmann: University of Applied Sciences Upper Austria
Klaus Altendorfer: University of Applied Sciences Upper Austria
Thomas Felberbauer: University of Applied Sciences St. Pölten

A chapter in Operations Research Proceedings 2021, 2022, pp 421-426 from Springer

Abstract: Abstract This paper investigates the effects of rolling horizon forecast updates on a production system relying on material requirements planning (MRP). The underlying demand model is the MMFE (martingale model of forecast evolution) model extended by forecast biases revealed certain periods before delivery, i.e. information quality is not strictly increasing as assumed in MMFE. Simulation is applied to model the MRP planning method and the shop floor behavior of a two stage production system including a two level bill-of-materials with 8 finished goods and 4 semi-finished materials. Several scenarios on the demand model parameterization are tested and a finite solution space for the MRP planning parameter safety stock is enumerated to minimize overall costs. In this numerical study, preliminary results to identify the influence of forecast uncertainty on MRP planning parameter safety stock are identified when rolling horizon forecast updates occur.

Keywords: Forecast errors; Production planning; Production order accuracy; Forecast evolution; Simulations (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-031-08623-6_62

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DOI: 10.1007/978-3-031-08623-6_62

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