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Demand signal modelling: A short-range panel forecasting algorithm for semiconductor firm device-level demand
Arizona State University, Tempe.
Division of Mathematical and Natural Sciences, Arizona State University, Arizona State University, Tempe.
Arizona State University, Tempe.
Arizona State University, Tempe.ORCID iD: 0000-0003-4222-9631
2008 (English)In: European Journal of Industrial Engineering, ISSN 1751-5254, E-ISSN 1751-5262, Vol. 2, no 3, p. 253-278Article in journal (Refereed) Published
Abstract [en]

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

Place, publisher, year, edition, pages
2008. Vol. 2, no 3, p. 253-278
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
URN: urn:nbn:se:ltu:diva-7606DOI: 10.1504/EJIE.2008.017686ISI: 000266125800002Scopus ID: 2-s2.0-41749121495Local ID: 5ff1c32f-cc47-4e64-b289-b5d0ebfcdbc1OAI: oai:DiVA.org:ltu-7606DiVA, id: diva2:980496
Note
Upprättat; 2008; 20150529 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2023-05-08Bibliographically approved

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Kulahci, Murat

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