Patent Document ID: 7962234
Application ID: 12135522
Patent Flag: 1

Claim One:
1. A method for optimizing multiple process windows, each process window corresponding to a different process parameter, in a semiconductor manufacturing process, comprising the steps of: performing dependent variable composition on a plurality of dependent variables; retrieving metrology data for each process parameter; joining the plurality of dependent variables and the metrology data to form a joined data set; performing a partial least squares regression on the joined data set to obtain a prediction equation, and a variable importance prediction for each process parameter; generating a process target value for each parameter, based on the value of the corresponding variable importance prediction; generating a new process window for each parameter, based on the corresponding process target value, thereby forming a process window set; evaluating the process window set by deriving a plurality of product limited yield values based on a negative binomial yield model, and comparing it to the plurality of product limited yield values derived with a previous process window set, and computing a predicted product yield value based on the product of the plurality of product limited yield values; and repeating the steps of generating a process target value for each parameter, based on the value of the corresponding variable importance prediction and generating a new process target window for each parameter, based on the corresponding process target value until, the predicted product yield value has reached an optimal value, thereby deriving an optimized process window set, and further comprising the steps of: generating a plurality of bucket indices, wherein each of the plurality of bucket indices corresponds to a bucket, and each bucket corresponds to a process window, and each process window overlaps with the process window of at least one adjacent bucket index; and wherein the step of evaluating the process window set by deriving a process yield value based on data corresponding to the process window set comprises inputting bucket observation values into the prediction equation.