Nonnegative Matrix Factorization for Binary Data to Extract Elementary Failure Maps from Wafer Test Images Export

@incollection{citeulike:5989147, abstract = {We introduce a probabilistic variant of nonnegative matrix factorization (NMF) applied to binary datasets. Hence we consider binary coded images as a probabilistic superposition of underlying continuous-valued basic patterns. An extension of the well-known NMF procedure to binary-valued datasets is provided to solve the related optimization problem with nonnegativity constraints. We demonstrate the performance of our method by applying it to the detection and characterization of hidden causes for failures during wafer processing. Therefore, we decompose binary coded (pass/fail) wafer test data into underlying elementary failure patterns and study their influence on the quality of single wafers.}, author = {Schachtner, Reinhard and P\"{o}ppel, Gerhard and Lang, Elmar}, citeulike-article-id = {5989147}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-642-01044-6_69}, citeulike-linkout-1 = {http://www.springerlink.com/content/w6528h460w58wq64}, doi = {10.1007/978-3-642-01044-6_69}, journal = {Advances in Data Analysis, Data Handling and Business Intelligence}, keywords = {manufacturing, nmf}, pages = {755--764}, posted-at = {2009-10-22 19:53:35}, priority = {2}, title = {Nonnegative Matrix Factorization for Binary Data to Extract Elementary Failure Maps from Wafer Test Images}, url = {http://dx.doi.org/10.1007/978-3-642-01044-6_69}, year = {2010} }

TY - CHAP ID - citeulike:5989147 L3 - citeulike-article-id:5989147 N2 - We introduce a probabilistic variant of nonnegative matrix factorization (NMF) applied to binary datasets. Hence we consider binary coded images as a probabilistic superposition of underlying continuous-valued basic patterns. An extension of the well-known NMF procedure to binary-valued datasets is provided to solve the related optimization problem with nonnegativity constraints. We demonstrate the performance of our method by applying it to the detection and characterization of hidden causes for failures during wafer processing. Therefore, we decompose binary coded (pass/fail) wafer test data into underlying elementary failure patterns and study their influence on the quality of single wafers. JF - Advances in Data Analysis, Data Handling and Business Intelligence EP - 764 TI - Nonnegative Matrix Factorization for Binary Data to Extract Elementary Failure Maps from Wafer Test Images SP - 755 KW - manufacturing KW - nmf AU - Schachtner, Reinhard AU - Pöppel, Gerhard AU - Lang, Elmar PY - 2010/// UR - http://dx.doi.org/10.1007/978-3-642-01044-6_69 ER -