METHOD AND SYSTEM FOR SEMICONDUCTOR PROCESS CONTROL AND MONITORING BY USING PCA MODELS OF REDUCED SIZE
First Claim
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1. A method, comprising:
- obtaining a plurality of historical measurement data sets, each of said plurality of historical measurement data sets related to a respective parameter set and measured during processing of semiconductor devices in a manufacturing environment;
establishing a model for each respective parameter set by using a principal component analysis technique and a respective one of said plurality of measurement data sets related to said respective parameter set;
obtaining a first measurement data set corresponding to a first parameter set of said parameter sets;
obtaining a second measurement data set corresponding to a second parameter set of said parameter sets;
applying a first model corresponding to said first parameter set to said first measurement data set;
applying a second model corresponding to said second parameter set to said second measurement data set; and
evaluating said first and second measurement data sets by combining a first statistical value set obtained from said first model and a second statistical value set obtained from said second model.
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Abstract
By dividing a complex set of parameters of a production process in forming semiconductor devices into individual blocks, respective PCA models may be established for each block and may thereafter be combined by operating on summary statistics of each model block in order to evaluate the complete initial parameter set. Thus, compared to conventional strategies, a significant reduction of the size of the combined PCA model compared to a single PCA model may be obtained, while also achieving an enhanced degree of flexibility in evaluating various subsets of parameters.
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Citations
20 Claims
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1. A method, comprising:
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obtaining a plurality of historical measurement data sets, each of said plurality of historical measurement data sets related to a respective parameter set and measured during processing of semiconductor devices in a manufacturing environment; establishing a model for each respective parameter set by using a principal component analysis technique and a respective one of said plurality of measurement data sets related to said respective parameter set; obtaining a first measurement data set corresponding to a first parameter set of said parameter sets; obtaining a second measurement data set corresponding to a second parameter set of said parameter sets; applying a first model corresponding to said first parameter set to said first measurement data set; applying a second model corresponding to said second parameter set to said second measurement data set; and evaluating said first and second measurement data sets by combining a first statistical value set obtained from said first model and a second statistical value set obtained from said second model. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method of fault detection in a semiconductor manufacturing process sequence, the method comprising:
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applying a first PCA model to a first set of measurement data related to a process result of said semiconductor manufacturing process sequence and corresponding to a first parameter set; determining a first set of summary statistical values for evaluating said first parameter set; applying a second PCA model to a second set of measurement data related to said process result of said semiconductor manufacturing process sequence and corresponding to a second parameter set; determining a second set of summary statistical values for evaluating said second parameter set; and combining said first and second sets of summary statistical values so as to commonly evaluate said first and second measurement data. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19)
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20. A fault detection system, comprising:
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a database comprising a plurality of PCA models and a corresponding set of statistical key values obtained by applying each PCA model to a respective set of measurement data corresponding to a respective set of process parameters to be monitored during the processing of semiconductor devices; and a fault detection module connected to said database and configured to retrieve summary statistics of at least some of said PCA models and to combine said at least some summary statistics to provide a combined statistical evaluation of at least some of said parameter sets.
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Specification