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.
Highlights
Inventory control is an essential element within the discipline of operations management and serves to ensure sufficient parts and raw materials are available for immediate production needs while minimising the overall stock holding at the point of production and throughout the supply chain
The paper reviews the application of both time series analysis and a Monte Carlo simulation method to construct a robust forecast for the shell usage consumption
The purchasing professionals within the case study environment having no experience of applying formal forecasting methods placed orders on the crankshaft shell suppliers that were effectively a “best guess”
Summary
Inventory control is an essential element within the discipline of operations management and serves to ensure sufficient parts and raw materials are available for immediate production needs while minimising the overall stock holding at the point of production and throughout the supply chain. This paper presents a study of an inventory process that does not fit into the standard inventory models within conventional operations management or for service and spare parts management. How to cite this paper: Davies, R., et al (2014) The Application of Time Series Modelling and Monte Carlo Simulation: Forecasting Volatile Inventory Requirements. The paper reviews the application of both time series analysis and a Monte Carlo simulation method to construct a robust forecast for the shell usage consumption. The analysis utilises usage data provided by a volume engine manufacturer over a 109-week production build period
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