{"id":29723,"date":"1998-10-04T16:26:00","date_gmt":"1998-10-04T16:26:00","guid":{"rendered":"https:\/\/silvaco.com\/uncategorized\/spayn-recent-developments\/"},"modified":"2021-07-08T18:47:59","modified_gmt":"2021-07-09T01:47:59","slug":"spayn-recent-developments","status":"publish","type":"post","link":"https:\/\/silvaco.com\/ja\/simulation-standard\/spayn-recent-developments\/","title":{"rendered":"SPAYN Recent Developments"},"content":{"rendered":"
\n

SPAYN Recent Developments<\/h1>\n

Introduction<\/p>\n

An important aspect of statistical process control in IC production is the ability to predict circuit performance variation in the manufacturing process. Two new features in\u00a0SPAYN<\/b>\u00a0allow the user, for a particular circuit performance parameter, to rapidly calculate an estimate of the standard deviation and also generate a yield distribution utilising Monte Carlo simulations, thus allowing a full statistical analysis of the circuit performance parameter distribution.<\/p>\n

For any given data base containing SPICE model parameters, an initial exploratory data analysis usually consists of trying to identify relationships and interdependencies between the specified variables. This is usually achieved by looking at the correlation structure, and examining histogram and scattergram plots of the various circuit parameters. However due to the large number of SPICE model parameters that are generally extracted, it is of great benefit to be able to generate these plots automatically. The new\u00a0SPAYN<\/b>\u00a0“Macro Command” feature allows the user to do just that.<\/p>\n<\/div><\/section><\/div>

<\/div>