Method and apparatus for setting semiconductor device manufacturing parameter

An apparatus for determining a semiconductor device manufacturing parameter, the apparatus comprising:

• a pre-processing module and an analysis module,
• wherein the pre-processing module is configured to:
• determine an EPM (electrical measurement parameter) group that has a correlation in a baseline EPM dataset, the baseline EPM including a plurality of EPMs measured from a baseline semiconductor device manufactured under a baseline condition corresponding to a basic experimental condition for setting semiconductor device manufacturing parameters,
• derive a plurality of principal components (PCs) corresponding to main correlation axes between EPMs in the EPM group by performing data component analysis on the EPM group, and
• derive a PC-based dataset including a conditional split PC dataset and a baseline PC dataset by converting a conditional split EPM dataset and the baseline EPM dataset into to a PC domain corresponding to the plurality of PCs, the conditional split EPM dataset including a plurality of EPMs measured from each of a plurality of conditional split semiconductor devices manufactured under a plurality of conditional splits having the conditions changed from the baseline condition;
• and
• wherein the analysis module is configured to:
• determine a PC which is effectively changed by each of the plurality of conditional splits through data processing on the PC-based dataset,
• obtain split variation information caused by each of the plurality of conditional splits,
• extract an optimal point capable of optimizing a figure of merit (FOM) of a semiconductor device within a range of the PC-based dataset, and
• derive information for process feedback for implementing the optimal point using the split variation information.

A non-transitory computer readable storage medium including a computer program, the computer program including one or more instructions, the one or more instructions, when executed by a computing device having one or more processors, causes the computing device to:

• determine an EPM (electrical measurement parameter) group that has a correlation in a baseline EPM dataset including a plurality of EPMs measured from a baseline semiconductor device manufactured under a baseline condition corresponding to a basic experimental condition for setting semiconductor device manufacturing parameters;
• derive a plurality of principal components (PCs) corresponding to main correlation axes between EPMs in the EPM group by performing data component analysis on the EPM group;
• derive a PC-based dataset including a conditional split PC dataset and a baseline PC dataset by converting a conditional split EPM dataset and the baseline EPM dataset into to a PC domain corresponding to the plurality of PCs derived by the data component analysis applied to the baseline EPM dataset, the conditional split EPM dataset including a plurality of EPMs measured from each of a plurality of conditional split semiconductor devices manufactured under a plurality of conditional splits having the conditions changed from the baseline condition;
• determine a PC which is effectively changed by each of the plurality of conditional splits through data processing on the PC-based dataset, and obtain split variation information caused by each of the plurality of conditional splits;
• extract an optimal point capable of optimizing a figure of merit (FOM) of a semiconductor device within a range of the PC-based dataset;
• and
• derive information for process feedback for implementing the optimal point using the split variation information.