Prediction of customer demands for production planning – Automated selection and configuration of suitable prediction methods

Abstract

Demand planning is of significant importance for manufacturing companies since subsequent steps of production planning base on demand forecasts. Major tasks of demand planning are the selection of a prediction method and the configuration of its parameters subject to a given demand evolution. This paper introduces a novel method for the automated selection and configuration of suitable prediction methods for time series of customer demands. The research investigates correlations between dynamic time series characteristics and forecasting accuracies of different prediction methods. The evaluation of the method on a database comprising real industry data confirms excellent prediction results.