Title: Demand signal modelling: a short-range panel forecasting algorithm for semiconductor firm device-level demand

Authors: Russell J. Elias, Douglas C. Montgomery, Stuart A. Low, Murat Kulahci

Addresses: Arizona State University, USA. ' Arizona State University, USA. ' Arizona State University, USA. ' Arizona State University, USA

Abstract: A model-based approach to the forecasting of short-range product demand within the semiconductor industry is presented. Device-level forecast models are developed via a novel two-stage stochastic algorithm that permits leading indicators to be optimally blended with smoothed estimates of unit-level demand. Leading indicators include backlog, bookings, delinquencies, inventory positions, and distributor resales. Group level forecasts are easily obtained through upwards aggregation of the device level forecasts. The forecasting algorithm is demonstrated at two major US-based semiconductor manufacturers. The first application involves a product family consisting of 254 individual devices with a 26-month training dataset and eight-month ex situ validation dataset. A subsequent demonstration refines the approach, and is demonstrated across a panel of six high volume devices with a 29-month training dataset and a 13-month ex situ validation dataset. In both implementations, significant improvement is realised versus legacy forecasting systems. [Received 11 May 2007; Revised 5 September 2007; Accepted 15 October 2007]

Keywords: demand forecasting; statistical forecasting; enterprise resource planning; ERP; supply chain management; SCM; operations modelling; semiconductor fabrication; demand signal modelling; panel forecasting algorithm; device-level demand.

DOI: 10.1504/EJIE.2008.017686

European Journal of Industrial Engineering, 2008 Vol.2 No.3, pp.253 - 278

Published online: 26 Mar 2008 *

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