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2010
Conference Paper
Titel
Virtual prototyping advanced by statistic and stochastic methodologies
Abstract
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.