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首页> 外文期刊>Applied Mathematics >The Application of Time Series Modelling and Monte Carlo Simulation: Forecasting Volatile Inventory Requirements
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The Application of Time Series Modelling and Monte Carlo Simulation: Forecasting Volatile Inventory Requirements

机译：时间序列建模和蒙特卡洛模拟的应用：预测挥发性库存需求

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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.
机译：在内燃机组装期间，直到将曲轴安装到发动机缸体之前，才知道曲轴箱轴承的具体尺寸。尽管对发动机的构造要求是一致的，但由于曲轴和发动机缸体尺寸的微小变化，不同尺寸的轴瓦轴承的消耗曲线可能会遵循高度波动的轨迹。本文评估了包括ARIMA和指数平滑在内的时间序列模型的适用性，以此作为预测未来需求的适当方法。此外，通过在Microsoft Excel中构建VBA仿真工具并将输出与时间序列预测进行比较，可以应用Monte Carlo方法。

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