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Communication Dans Un Congrès Année : 2011

Dependability of complex semiconductor systems : Learning Bayesian Networks for decision support

Éric Zamaï
F. Duvivier
  • Fonction : Auteur
  • PersonId : 923455
S. Hubac
  • Fonction : Auteur
  • PersonId : 923456

Résumé

The production of microelectronic components is characterized by an important complexity of production context, high technology renewal cadence, a strong customer requirement and an uncertain environment. This has an impact on the cycle time, costs and equipment efficiencies. This paper presents a general methodology to manage the risks of complex semiconductors systems. A literature review about process control, risk analysis methods and Bayesian networks is presented. A first structure of the predictive behavior model is proposed, this model is based on Bayesian learning methods.
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Dates et versions

hal-00683047 , version 1 (27-03-2012)

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Citer

Mohammed Farouk Bouaziz, Éric Zamaï, F. Duvivier, S. Hubac. Dependability of complex semiconductor systems : Learning Bayesian Networks for decision support. Third International Workshop on Dependable Control of Discrete Systems (DCDS 2011), Jun 2011, Saarbüken, Germany. paper N°41, pp 09 - 14,, ⟨10.1109/DCDS.2011.5970310⟩. ⟨hal-00683047⟩
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