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The Application of Time Series Modelling and Monte Carlo Simulation: Forecasting Volatile Inventory Requirements 被引量:1

The Application of Time Series Modelling and Monte Carlo Simulation: Forecasting Volatile Inventory Requirements
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摘要 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. 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.
出处 《Applied Mathematics》 2014年第8期1152-1168,共17页 应用数学(英文)
关键词 Forecasting Time Series Analysis MONTE Carlo Simulation Forecasting Time Series Analysis Monte Carlo Simulation
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