SeDFAM: semiconductor demand forecast accuracy model

Abstract

In the semiconductor industry, many critical decisions are based on demand forecasts. However, these forecasts are subject to random error. In this paper, we lay out a scheme estimating the variance and correlation of forecast errors (without altering given forecasts) and modeling the evolution of forecasts over time. Our scheme allows correlations across time, products and technologies. It also addresses the case of nonstationary errors due to ramps (technology migrations). It can be used to simulate chip demands for production planning/capacity expansion studies.