Click here to go to a list of just the titles of these articles.

• Statistically Based Parametric Yield Prediction for Integrated Circuits Gibson, Podder, May, and Brooke

  -Georgia Tech folks -Good article -suggests using multivariate distribution with covariance rather than "multinormal" (I think they mean independent normals by this word) -use discretized space and small number of runs to reproducibly get curves (by reproducible, there isn't any random component in simulation) -competition for Monte Carlo when don't want to spend a lot of money.

• Yield Modeling of Acoustic Charge Transport Transversal Filters Kenny, May, and Hunt

  -Georgia Tech folks again -Question - What are taps? I think they are multiple sensors that are placed in circuit -Acoustic Charge Transport (ACT) has yield problems that if controlled could make it a more promising technology -One factor that is explored is the redundancy of taps because it results in a tradeoff of improved yield for more taps except that too many taps results in larger die size and hence a smaller yield -concentrated on missing taps (ie metal being missing in some protion) which does not mean device failure necessarily (ie soft failure); explored how many taps could be reduced without hurting circuit enough to make out of spec (effective redundancy) -used poisson yield model -predicted yield as a function of defect density fairly well -however although Monte Carlo simulations agree on the yield model, they got differing recommendations for redundancy which was primary goal

• Semiconductor Yield Improvement: Results and Best Practices Cunningham, Spanos, and Voros

  -did worldwide survey to assess what factors influence yield -define yield as fraction of total input transformed into shippable output -three types of yield and product of these is overall yield (ie yield = die yield*line yield*final test yield) -identified good practices such as automation of SPC, in house yield models, and yield groups, etc.

Back to Home Page.