A Comparative Analysis of the D041 System and Time Series Analysis Models for Forecasting Reparable Item Generations.

摘要

This research effort compared the D041 Single Moving Average Forecasting method used to forecast reparable generations of recoverable items with the Box and Jenkin's Time Series Analysis forcasting methods. Five artificially generated stochastic processes were used to model the possible reparable generations observed in practice: (1) a Poisson process with a constant mean, (2) a Poisson process with a decreasing mean, (4) a Poisson process with an alternating linear mean, and (5) a process whose values are the sine function of the output of a Poisson process. The reserach concluded that the D041 forecasting mthod made unbiased forecasts for the Poisson process with a constant mean and the sine function, but made biased forecasts for the other three processes. Time Series Analysis forecasting methods were only used to make forecasts for the processes that were found to be biased using the D041 forecasting method. Time Series Analysis forecasting methods made unbiased forecasts for the processes whose means were linearly increasing, linearly decreasing, and alternating linearly.