TITLE:
The Application of Time Series Modelling and Monte Carlo Simulation: Forecasting Volatile Inventory Requirements
AUTHORS:
Robert Davies, Tim Coole, David Osipyw
KEYWORDS:
Forecasting, Time Series Analysis, Monte Carlo Simulation
JOURNAL NAME:
Applied Mathematics,
Vol.5 No.8,
May
5,
2014
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.