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Virtual prototyping advanced by statistic and stochastic methodologies

: Rzepka, S.; Müller, A.; Michel, B.


Institute of Electrical and Electronics Engineers -IEEE-:
11th international thermal, mechanical & multi-physics simulation, and experiments in microelectronics and microsystems, EuroSimE 2010 : Bordeaux / France; 26.-28.04.2010
Piscataway/NJ: IEEE, 2010
ISBN: 978-1-4244-7026-6
ISBN: 978-1-4244-7027-3
International Conference on Thermal, Mechanical & Multi-Physics Simulation, and Experiments in Microelectronics and Microsystems (EuroSimE) <11, 2010, Bordeaux>
Fraunhofer ENAS ()

The paper reports three examples of best industrial practice showing the substantial benefits gained in terms of time-to-market reduction when virtual prototyping is enhanced by statistical and stochastic methodologies. These examples from a microelectronics setting of high volume component and module manufacturing deal with different fields: i) ball grid array (BGA) design optimization based on sophisticated design-of-experiments (DoE) and response surface (RS) schemes, ii) material modeling based on stochastic parameter identification and optimization, and iii) process pre-qualification by involving a stochastic robustness analysis.