Forecast facilitated lot-for-lot ordering in the presence of autocorrelated demand

Abstract

With consistent effort in setup reduction as encouraged by JIT principle, lot-for-lot ordering is gaining popularity in MRP applications. A lot-for-lot order is an immediate copy of the MPS (master production schedule) – direct reflection of demand forecasts. Since all levels of MRP plans are based on MPS, the accuracy of MRP is highly dependent of the accuracy of demand forecasting. In this paper, we are concerned about the impact of forecasting to the performance of a lot-for-lot MRP system when there is notable variability and autocorrelation in the underlying demand process (e.g., an AR(1) process). Specifically under a stationary AR(1) demand, we examine the performance of the MRP based on the most common EWMA forecast model, and then compare it with a minimum mean square error (MSE) forecast model. The notable findings of this study include: (1) MRP performance differs noticeably under the two different forecasting models. (2) The MSE-optimal forecasting performs no worse than the EWMA forecasting in all aspects of MRP applications.