Title :
Dependability of complex semiconductor systems: Learning Bayesian networks for decision support
Author :
Bouaziz, Mohammed Farouk ; Zamai, Eric ; Duvivier, Frederic ; Hubac, Stéphane
Author_Institution :
G-SCOP, CNRS, Grenoble, France
Abstract :
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.
Keywords :
belief networks; control engineering computing; decision support systems; learning (artificial intelligence); process control; production engineering computing; risk analysis; semiconductor device manufacture; Bayesian learning methods; Bayesian networks; complex semiconductor system dependability; costs efficiencies; customer requirement; cycle time; decision support; equipment efficiencies; microelectronic component production; predictive behavior model; process control; production context complexity; renewal cadence; risk analysis methods; Bayesian methods; Maintenance engineering; Manufacturing; Metrology; Predictive models; Production; Risk analysis; Bayesian networks; complex semiconductor systems; decision support; dependability; learning;
Conference_Titel :
Dependable Control of Discrete Systems (DCDS), 2011 3rd International Workshop on
Conference_Location :
Saarbrucken
Print_ISBN :
978-1-4244-8969-5
DOI :
10.1109/DCDS.2011.5970310
