Electronic Design, Test and Applications, IEEE International Workshop on (2011)
Queenstown, New Zealand
Jan. 17, 2011 to Jan. 19, 2011
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DELTA.2011.53
Recurring defect cluster patterns on semiconductor wafers can be linked to imperfectness/faults in specific manufacturing processes or alternatively-to failure or malfunctioning of production equipment (in our research we assume that defects associated with deficiencies/errors in the circuit design are not present). By identifying these patterns as they occur, a fast and effective process monitoring and control mechanism can be achieved, shortening the time-to-yield period and reducing the loss in revenue due to avoidable yield drop. Identifying these patterns manually could be a too complex and time consuming task. This research presents an automatic yield management system to extract and identify defect clusters as well as perform yield analysis in a high-volume semiconductor devise manufacturing.
semiconductor device manufacture, failure analysis, process control, process monitoring, production equipment, productivity, production equipment failure, automatic yield management system, semiconductor production testing, process monitoring, process control mechanism, revenue loss reduction, defect clusters identification, semiconductor device manufacturing, semiconductor wafers, manufacturing process faults, production equipment malfunctioning, Classification algorithms, Manufacturing, Feature extraction, Production, Integrated circuits, Classification tree analysis, yield analysis, semiconductor wafer technology, yield management, defect clusters
"Automatic Yield Management System for Semiconductor Production Test," 2011 IEEE 6th International Workshop on Electronic Design, Test and Application (DELTA 2011)(DELTA), Queenstown, 2011, pp. 254-258.