The Application of Time Series Modelling and Monte Carlo Simulation: Forecasting Volatile Inventory Requirements

Robert Davies, Tim Coole, David Osipyw

Faculty of Design Media and Management, Buckinghamshire New University, High Wycombe, UK.

DOI: 10.4236/am.2014.58108                

Abstract

During the assembly of internal combustion engines, the specific size of crankshaft shell bearing is not known until the crankshaft is fitted to the engine block. Though the build requirements for the engine are consistent, the consumption profile of the different size shell bearings can follow a highly volatile trajectory due to minor variation in the dimensions of the crankshaft and engine block. The paper assesses the suitability of time series models including ARIMA and exponential smoothing as an appropriate method to forecast future requirements. Additionally, a Monte Carlo method is applied through building a VBA simulation tool in Microsoft Excel and comparing the output to the time series forecasts.

Keywords

Forecasting, Time Series Analysis, Monte Carlo Simulation

Conflicts of Interest

The authors declare no conflicts of interest.

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