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In this paper we propose spatial modeling approaches for clustered defects observed using an Integrated Circuit (IC) wafer map. We use the spatial location of each IC chip on the wafer as a covariate for the corresponding defect count listed in the wafer map. Our models are based on a Poisson regression, a negative binomial regression, and Zero-Inflated Poisson (ZIP) regression. Analysis results indicate that yield prediction can be greatly improved by capturing the spatial distribution of defects across the wafer map. In particular, the ZIP model with spatial covariates shows considerable promise as a yield model since it additionally models zero-defective chips. The modeling procedures are tested using a practical example. Keywords: Generalized linear models, negative binomial regression, spatial clustering, wafer map, yield, zero-inflated Poisson regression, 1. Introduction Integrated circuit (IC) processes and production equipment have undergone tremendous changes over time, fostering rapid technological advances throughout the industry. The semiconductor industry has been able to double [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2005.11.032 Byline: Jung Yoon Hwang (a), Way Kuo (b) Keywords: Quality control; Stochastic processes Abstract: This paper studies the defect data analysis method for semiconductor yield enhancement. Given the defect locations on a wafer, the local defects generated from the assignable causes are classified from the global defects generated from the random causes by model-based clustering, and the clustering methods can identify the characteristics of local defect clusters. The information obtained from this method can facilitate process control, particularly, root-cause analysis. The global defects are modeled by the spatial non-homogeneous Poisson process, and the local defects are modeled by the bivariate normal distribution or by the principal curve. Author Affiliation: (a) Samsung Electronics, Hwasung-City 445-701, Republic of Korea (b) The University of Tennessee, College of Engineering, 124 Perkins Hall, Knoxville, TN 37996-2000, United States Article History: Received 16 November 2004; Accepted 30 November 2005