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

Author

Listed:
  • Russell J. Elias
  • Douglas C. Montgomery
  • Stuart A. Low
  • Murat Kulahci

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]

Suggested Citation

  • Russell J. Elias & Douglas C. Montgomery & Stuart A. Low & Murat Kulahci, 2008. "Demand signal modelling: a short-range panel forecasting algorithm for semiconductor firm device-level demand," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 2(3), pages 253-278.
    • Handle: RePEc:ids:eujine:v:2:y:2008:i:3:p:253-278
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