An experimental methodology for the estimation of spatially correlated parametric yield in thin film devices

In this paper we present an experimental methodology for parametric yield estimation that accounts for spatial correlations between features of the same device at specific wafer locations. Each device feature is representative of a device parameter that must fit with a specific tolerance box and may be influenced by several steps of the manufacturing process. If the process how is known and each of its steps is characterized in a spatially correlated manner, the feature pointwise probability density functions (PDFs) can be accurately reconstructed from the processing step pointwise PDFs. This method thus permits the estimation of pointwise device yield more accurately than the common multilevel (run, wafer, die) averaging approach. Because spatially correlated phenomena is subject to both random and systematic nonuniformities, the pointwise step (PDFs) are determined by a decomposition process that separates the systematic and random error components. The systematic PDFs are determined from interpolation functions representing the spatial variations across the entire wafer lot, and the random PDFs are approximated using a combination of principle component analysis and factor analysis with a few uncorrelated random variables valid for the entire lot.