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; Thomas Felberbauer

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, Thomas Felberbauer

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

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.

Translated title of the contribution	Influence of Forecast Error and Forecast Bias on Safety Stock on a MRP System with Rolling Horizon Forecast Updates
Original language	English
Title of host publication	Operations Research Proceedings 2021
Publisher	Springer
Pages	421-426
Publication status	Published - 30 Aug 2022

Publication series

Name	Lecture Notes in Operations Research
ISSN (Print)	2731-040X
ISSN (Electronic)	2731-0418

Cite this

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

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.",

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Influence of Forecast Error and Forecast Bias on Safety Stock on a MRP System with Rolling Horizon Forecast Updates. / Seiringer, Wolfgang; Brockmann, Fabian; Altendorfer, Klaus et al.
Operations Research Proceedings 2021. Springer, 2022. p. 421-426 (Lecture Notes in Operations Research).

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

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T1 - Influence of Forecast Error and Forecast Bias on Safety Stock on a MRP System with Rolling Horizon Forecast Updates

AU - Seiringer, Wolfgang

AU - Brockmann, Fabian

AU - Altendorfer, Klaus

AU - Felberbauer, Thomas

PY - 2022/8/30

Y1 - 2022/8/30

N2 - 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.

AB - 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.

M3 - Conference contribution

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BT - Operations Research Proceedings 2021

PB - Springer

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