Mks Instruments, Inc.

Kuo-Chin Lin

Lawrence Hendler

Svante Bjarne Wold

A method for monitoring a manufacturing process features acquiring metrology data for semiconductor wafers at the conclusion of a final process step for the manufacturing process ('Step a'). Data is acquired for a plurality of process variables for a first process step for manufacturing semiconductor wafers ('Step b'). A first mathematical model of the first process step is created based on the metrology data and the acquired data for the plurality of process variables for the first process step (&#x201c;Step c&#x201d;). Steps b and c are repeated for at least a second process step for manufacturing the semiconductor wafers (&#x201c;Step d&#x201d;). An nth mathematical model is created based on the metrology data and the data for the plurality of process variables for each of the n process steps ('Step e&#x201c;). A top level mathematical model is created based on the metrology data and the models created by steps c, d and e (&#x201d;Step f'). The top level mathematical model of Step f is based on those process variables that have a substantial effect on the metrology data.

Process control using process data and yield data

A method for monitoring a manufacturing process features acquiring metrology data for semiconductor wafers at the conclusion of a final process step for the manufacturing process ('Step a'). Data is acquired for a plurality of process variables for a first process step for manufacturing semiconductor wafers ('Step b'). A first mathematical model of the first process step is created based on the metrology data and the acquired data for the plurality of process variables for the first process step (&#x201c;Step c&#x201d;). Steps b and c are repeated for at least a second process step for manufacturing the semiconductor wafers (&#x201c;Step d&#x201d;). An nth mathematical model is created based on the metrology data and the data for the plurality of 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;). The top level mathematical model of Step f is based on those process variables that have a substantial effect on the metrology data.

A method for detecting a fault condition of a manufacturing process involving acquiring data and developing a model based on a plurality of manufacturing related variables for a plurality of outputs of a manufacturing process. The method also involves identifying which of the manufacturing related variables have a substantial affect on the model for detecting faulty outputs of the manufacturing process. The method also involves updating the model by using the manufacturing related variables identified as having a substantial affect on the model to improve the ability of the model to detect faulty outputs of the manufacturing process.

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Sacramento, CA, United States of America

Kuo-Chin Lin