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INDUSTRIAL IMPLEMENTATION OF A DYNAMIC SAMPLING ALGORITHM IN SEMICONDUCTOR MANUFACTURING: APPROACH AND CHALLENGES

Abstract : In a worldwide environment, sustaining high yield with a minimum number of quality controls is key for manufacturing plants to remain competitive. In high-mix semiconductor plants, where more than 200 products are concurrently run, the complexity of designing efficient control plans comes from the larger amount of data and number of production parameters to handle. Several sampling algorithms were pro-posed in the literature, but most of them are seen impracticable when coming to an industrial implemen-tation. In this paper, we present and discuss the industrial implementation of a dynamic sampling algo-rithm in a high-mix semiconductor plant. We describe how the sampling algorithm has been modified, and point out the set of questions that have been raised by the industrial program. Results indicate that more than 30% of control operations on lots could be avoided without increasing the material at risk in production.
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https://hal.archives-ouvertes.fr/hal-00719785
Contributor : Justin Nduhura <>
Submitted on : Friday, July 20, 2012 - 7:00:33 PM
Last modification on : Wednesday, June 24, 2020 - 4:19:21 PM

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  • HAL Id : hal-00719785, version 1

Citation

Justin Nduhura Munga, Stéphane Dauzère-Pérès, Philippe Vialletelle, Claude Yugma. INDUSTRIAL IMPLEMENTATION OF A DYNAMIC SAMPLING ALGORITHM IN SEMICONDUCTOR MANUFACTURING: APPROACH AND CHALLENGES. Modeling and Analysis of Semiconductor Manufacturing (MASM) Conference (included in Winter Simulation Conference), Dec 2012, Berlin, Germany. 9 p. ⟨hal-00719785⟩

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