Mks Instruments, Inc.

Lennart Eriksson

Svante Bjarne Wold

Johan Trygg

Tamara Byrne

A method for monitoring a manufacturing tool features acquiring metrology data ('Step a'). Data is acquired for process variables for a first process step performed by the manufacturing tool ('Step b'). A mathematical model of the first process step based on the metrology data and the acquired data is created (&#x201c;Step c&#x201d;). Steps b and c are repeated for at least a second process step (&#x201c;Step d&#x201d;). An nth mathematical model is created based on the metrology data and the data for the process variables for each of the n process steps (&#x201c;Step e&#x201d;). A top level mathematical model is created based on the metrology data and the models created by steps c, d and e (&#x201c;Step f&#x201d;). A multivariate metric is calculated based on the top level model of step f and data from subsequent runs of the manufacturing tool. Service is performed if the metric satisfies a condition.

Process control using process data and yield data

A method and system for partitioning (clustering) large amounts of data in a relatively short processing time. The method involves providing a first data matrix and a second data matrix where each of the first and second data matrices includes one or more variables, and a plurality of data points. The method also involves determining a first score from the first data matrix using a partial least squares (PLS) analysis or orthogonal PLS (OPLS) analysis and partitioning the first and second data matrices (e.g., row-wise) into a first group and a second group based on the sorted first score, the variance of the first data matrix, and a variance of the first and second groups relative to the variances of the first and second data matrices.

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Umea, Sweden

Lennart Eriksson