Title :
Statistical methodology for yield enhancement via baseline reduction
Author :
Fridgeirsdottir, Kristin ; Akella, Ram ; Li, Mien ; McNally, Peter ; Mittal, Sanjiv
Author_Institution :
Dept. of Eng., Stanford Univ., CA, USA
Abstract :
In this paper, we introduce a DOE-regression based methodology to identify which tools, in a segment of a fab line between two inspection stations, are defect generating. The approach estimates how much the yield could increase by repairing each of the tools. Furthermore, the tools can be ordered for repair according to this potential yield increase. The estimate of the yield increase includes an evaluation of the power of the statistical test performed to identify the defect generating tools, as well as the kill ratio. By identifying the problem-prone tools and repairing them in the order given by the estimated yield increase, the process baseline can be lowered in an effective manner and the yield increased
Keywords :
design of experiments; inspection; integrated circuit testing; integrated circuit yield; maintenance engineering; DOE-regression based methodology; baseline reduction; defect generating tools; estimated yield increase; fab line segment; inspection stations; kill ratio; problem-prone tool identification; process baseline; statistical methodology; statistical test power; tool repair; tool repair ordering; yield enhancement; Costs; Inspection; Operations research; Performance evaluation; Power generation; Sampling methods; Statistical analysis; Systems engineering and theory; Testing; Yield estimation;
Conference_Titel :
Advanced Semiconductor Manufacturing Conference and Workshop, 1998. 1998 IEEE/SEMI
Conference_Location :
Boston, MA
Print_ISBN :
0-7803-4380-8
DOI :
10.1109/ASMC.1998.731402