System and method for the automatic determination of critical parametric electrical test parameters for inline yield monitoring

• Main Authors: MAHESHWARY, SONU, LEGBAND, DALE, ROBINSON, JOHN CHARLES, BANERJEE, SAIBAL
• Format: Patent
• Language: Chinese; English
• Published: 01.08.2018
• Subjects: BASIC ELECTRIC ELEMENTS; CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION ORPROCESSING OF GOODS; CONTROL OR REGULATING SYSTEMS IN GENERAL; CONTROLLING; ELECTRIC SOLID STATE DEVICES NOT OTHERWISE PROVIDED FOR; ELECTRICITY; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; MEASURING; MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS; PHYSICS; REGULATING; SEMICONDUCTOR DEVICES; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS; TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINSTCLIMATE CHANGE; TESTING

Inline yield monitoring may include the use of one or more modules of algorithmic software. Inline yield monitoring may include the use of two related algorithmic software modules such as a learning and a prediction module. The learning module may learn critical PET (parametric electrical test) parameters from data of probe electrical test yields and PET attribute values. The critical PET parameters may best separate outliers and inliers in the yield data. The prediction module may use the critical PET parameters found by the learning module to predict whether a wafer is an inlier or an outlier in a probe test classification.