CORRECTED FINAL REJECTION
DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Summary
This action is responsive to the interview conducted on 04/28/2026. Applicant has submitted Claims 1-2 and 4-7 for examination.
Examiner finds the following: 1) Claims 1-2 and 4-7 are rejected; 2) no claims objected to; and 3) no claims allowable.
Corrected Final Rejection
Applicant and Examiner conducted a video conference on 04/28/2026. Examiner erroneously issued a 101 Rejection in the Final Action after noting that the claims did not rise to the level of a 101 Rejection in the Non-Final Action. Examiner apologizes for this error.
As such, Examiner issues this Corrected Final Rejection, which removes the erroneous 101 Rejection but maintains all other rejections as noted below.
Response to Arguments and Remarks
Examiner respectfully acknowledges Applicant's arguments, remarks, and amendments.
Applicant's arguments filed 09/12/2025 have been fully considered but they are not persuasive.
First, Applicant argues that Chamness fails disclose, in particular:
… combining the result of said first evaluation step and the result of said second evaluation step …
Upon review of Applicant’s remarks and Chamness, Examiner understands Chamness to disclose this limitation. In [0101]:
At 560, at least one statistical quantity is determined from the additional data and the PCA model. For example, the additional data can be forward projected onto the one or more principal components to determine a set of scores, and the set of scores can be backward projected onto the principal components to determine one or more residual errors. Utilizing either the set of scores in conjunction with the model set of scores, or the one or more residual errors, at least one statistical quantity can be determined. (emphasis added)
Chamness clearly takes a set of datum and uses it for forward functions, backwards projections, or even mere comparison. Chamness can take a first set of datum and use it to compare, modify, or in combination with a second set of datum. Thus, it is apparent to Examiner that Chamness discloses the above limitation, and therefore Examiner maintains the rejection.
Examiner notes that Applicant specifically calls out that the “adaptive modeling approach” of Chamness is “fundamentally different from the claimed method of combining results from two distinct evaluation steps.” That may be the case, but that language is not reflected in the claimed language. Examiner encourages Applicant to amend the claims to better show this difference.
Second, Applicant further argues that Chamness fails to disclose a method for selecting specific wavelengths and times from the OES (optical emission spectra) data.
More specifically, Applicant argues that Chamness is using data primarily for statistical process monitoring and fault detection. Generally, Examiner does not disagree with that characterization of Chamness, but, based on Examiner’s review, the whole point of Chamness is to monitor for errors. Chamness monitors multiple aspects of its system, including wavelength and time (See Chamness, FIG. 12, [0099], “data can, for example, include optical emission spectra, RF harmonics of voltage and/or current measurements or radiated RF emission, etc. Each observation can pertain to a substrate run, instant in time, time average, etc.”). As the goal of Chamness is to identify and reduce errors, that would include monitoring of wavelengths and duration, and would also move the system towards less error prone wavelengths and times, or, as Applicant might put it, which wavelengths and times are “optimal.” Thus, Examiner is not persuaded.
Third, Applicant argues that Chamness cannot identify which specific wavelengths and times are optimal for process control because it operates on transformed data (principal components) rather than on the original parameters.
Examiner finds this distinction to be largely irrelevant. Chamness is clearly able to detect various wavelengths (See Chamness, [0043]), and even if the sets of datum are transformed, the goal of Chamness is to reduce errors. As Examiner understands it, such knowledge of the inputs into the sets of datum would inherently allow Chamness to indicate more “optimal” wavelengths and times that are less prone to error. As such, Examiner is not persuaded.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 2, 4 and 7 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Chamness (US20050060103A1).
Regarding Claim 1, Chamness discloses:
An analysis method of identifying a wavelength and a time of plasma light-emission data, said wavelength and said time of said plasma light-emission data being to be used for the adjustment of an etching processing condition in a semiconductor etching processing for applying said etching processing to a semiconductor wafer using said plasma, said analysis method (Chamness, [0010], “a method of monitoring a processing system for processing a substrate during the course of semiconductor manufacturing,” and FIG. 12, [0099], method 500,), comprising:
an acquisition step (Chamness, [0010], acquiring data from the processing system for a plurality of observations, the data comprising a plurality of data parameters,” and FIG. 12, [0099], Step 510) of acquiring said plasma light-emission data indicating light-emission intensities at a plurality of different wavelengths and times (Chamness, FIG. 12, [0099], “data can, for example, include optical emission spectra, RF harmonics of voltage and/or current measurements or radiated RF emission, etc. Each observation can pertain to a substrate run, instant in time, time average, etc.”), said plasma light- emission data being measured under a plurality of different etching processing conditions, and being obtained at the time of said etching processing (Chamness, FIG. 5, [0056], “each set of data parameters for a given substrate run, or instant in time, can be stored as a row in a matrix {overscore (X)} and, hence, once the matrix {overscore (X)} is assembled, each row represents a different substrate run, or instant in time (or observation), and each column represents a different data parameter (or data variable) corresponding to the plurality of sensors 50”);
a first evaluation step (Chamness, [0010], “constructing a principal components analysis (PCA) model from the data, including centering coefficients,” and FIG. 12, [0100], Step 520) of evaluating the relationship between changes in said etching processing conditions and changes in said light-emission intensities at said plurality of different wavelengths and times with respect to said wavelengths and times of said plasma light-emission data (Chamness, FIG. 12, [0100], “At 520, a PCA model is constructed from the acquired data parameters by determining one or more principal components to represent the data at 530 and applying static centering and scaling coefficients, as described above, to the data parameters of the acquired data at 540,” [0044], “the sensor is capable of collecting 5550 wavelengths from 240 to 1000 nm,” and [0045], “a full emission spectrum can be recorded every 0.1 to 1.0 seconds”);
a second evaluation step (Chamness, [0010], “acquiring additional data from the processing system, the additional data having an additional observation of the plurality of data parameters,” and FIG. 12, [0101], Step 550) of evaluating the relationship between said light-emission intensities at said plurality of different wavelengths and times of said plasma light-emission data, and the etching processing result (Chamness, FIG. 12, [0099], “The data can, for example, comprise any measurable data parameter, and any statistic thereof (e.g., mean, standard deviation, skewness, kurtosis, etc.). Additional data can, for example, include optical emission spectra, RF harmonics of voltage and/or current measurements or radiated RF emission, etc. Each observation can pertain to a substrate run, instant in time, time average, etc. ,” and FIG. 12, [0101], “At 550, additional data is acquired from a processing system, and, at 555, adaptive centering and scaling coefficients are utilized when applying the PCA model to the acquired data parameters”); and
an identification step (Chamness, [0010], “constructing a principal components analysis (PCA) model from the data, including centering coefficients,” and FIG. 12, [0100], Step 520) of identifying said wavelength and said time of said plasma light-emission data based on combining the result of said first evaluation step and the result of said second evaluation step (Chamness, FIG. 12, [0100], “applying static centering and scaling coefficients, as described above, to the data parameters of the acquired data at 540, ” and [0101], “the additional data can be forward projected onto the one or more principal components to determine a set of scores, and the set of scores can be backward projected onto the principal components to determine one or more residual errors. Utilizing either the set of scores in conjunction with the model set of scores, or the one or more residual errors, at least one statistical quantity can be determined, such as the Q-statistic, or the Hotelling T.sup.2 parameter, for each additional observation”), said wavelength and said time of said plasma light-emission data being to be used for said adjustment of said etching processing condition (Chamness, [0010], “setting a control limit for the at least one statistical quantity,” “adjusting the scaling coefficients to produce updated adaptive scaling coefficients for each of the data parameters in the PCA model,” and “applying the updated adaptive scaling coefficients to each of the data parameters in the PCA model,”, and FIG. 12, [0099], “The processing system can, for example, be an etch system, or it may be another processing system as described in FIG. 1”).
Regarding Claim 2, Chamness discloses Claim 1 and Chamness further discloses:
… wherein, at said first evaluation step, said relationship between said changes in said etching processing conditions and said changes in said light-emission intensities at said plurality of different wavelengths and times with respect to said wavelengths and times of said plasma light-emission data is evaluated using a prediction error or a correlation coefficient (Chamness, FIG. 6A, [0081], “the control limit can be reset for each process run based on a predicted degradation of the PCA model,” FIG. 12, [0099], “The processing system can, for example, be an etch system, or it may be another processing system as described in FIG. 1,” and FIG. 12, [0101], “the set of scores can be backward projected onto the principal components to determine one or more residual errors”).
Regarding Claim 4, Chamness discloses Claim 3 and Chamness further discloses:
… wherein, at said second evaluation step, said relationship between said light-emission intensities at said plurality of different wavelengths and times of said plasma light-emission data, and said etching processing result is evaluated using a prediction error or a correlation coefficient (Chamness, FIG. 6A, [0081], “the control limit can be reset for each process run based on a predicted degradation of the PCA model,” and FIG. 12, [0101], “the set of scores can be backward projected onto the principal components to determine one or more residual errors”).
Regarding Claim 7, Chamness discloses Claim 1 and Chamness further discloses:
An analysis method of calculating an adjustment value of said etching processing condition so that said adjustment value becomes equal to a target value of said etching processing result (Chamness, [0056], “The process of mean-centering the data stored in a matrix column involves computing a mean value of the column elements and subtracting the mean value from each element. Moreover, the data residing in a column of the matrix can be normalized by determining the standard deviation of the data in the column”), said adjustment value being calculated using said relationship between said light-emission intensity of said plasma light-emission data at said wavelength and said time, and said etching processing result (Chamness, [0010], “setting a control limit for the at least one statistical quantity,” “adjusting the scaling coefficients to produce updated adaptive scaling coefficients for each of the data parameters in the PCA model,” and “applying the updated adaptive scaling coefficients to each of the data parameters in the PCA model”), said wavelength and said time being identified using said analysis method according to Claim 1 (Chamness, FIG. 12, [0099], “data can, for example, include optical emission spectra, RF harmonics of voltage and/or current measurements or radiated RF emission, etc. Each observation can pertain to a substrate run, instant in time, time average, etc.”).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 5-6 are rejected under 35 U.S.C. 103 as being unpatentable over Chamness (US20050060103A1).
Regarding Claim 5, Chamness discloses Claim 4 and Chamness further discloses:
… said prediction error or said correlation coefficient at said first evaluation step and said prediction error or said correlation coefficient at said second evaluation step being used in said function (Chamness, FIG. 12, [0101], “At 550, additional data is acquired from a processing system, and, at 555, adaptive centering and scaling coefficients are utilized when applying the PCA model to the acquired data parameters”).
Chamness discloses the above but does not explicitly disclose:
… wherein, at said identification step, said wavelength and said time of said plasma light-emission data are identified so that a function becomes equal to its minimum value, …
However, Chamness does disclose in [0099]:
The data can, for example, comprise any measurable data parameter, and any statistic thereof (e.g., mean, standard deviation, skewness, kurtosis, etc.)
It would have been obvious to PHOSITA before the effective filing date of the claimed invention to modify Chamness with setting the function to its minimal value. PHOSITA would have known about the uses of various manners to apply deviations and how to use them to modify Chamness. PHOSITA would have been motivated to do this as an application of a known technique to a known (device, method, or product) ready for improvement to yield predictable results (See MPEP § 2143 (I)(D)), specifically the use of standard deviations and data anchoring in modelling and analysis.
Regarding Claim 6, Chamness discloses Claim 4 and Chamness further discloses:
… wherein said wavelength and said time of said plasma light-emission data are identified so that the sum total of said prediction error at said first evaluation step, said product being obtained by multiplying said prediction error at said second evaluation step by a coefficient (Chamness, [0069], “Similarly, the Hotelling T2 can be calculated as follows:
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”, said coefficient indicating said relationship between said light-emission intensities at said plurality of different wavelengths and times of said plasma light-emission data, and said etching processing result (Chamness, [0072], “a PCA model (loadings matrix {overscore (P)}, etc.) can be constructed using a "training" set of data (i.e. assemble {overscore (X)} for a number of observations and determine a PCA model using MATLAB.TM.). Once the PCA model is constructed, projections of a new observation onto the PCA model can be utilized to determine a new scores matrix {overscore (T)}”).
Chamness discloses the above but does not explicitly disclose:
…and a product becomes equal to its minimum value …
However, Chamness does disclose in [0099]:
The data can, for example, comprise any measurable data parameter, and any statistic thereof (e.g., mean, standard deviation, skewness, kurtosis, etc.)
It would have been obvious to PHOSITA before the effective filing date of the claimed invention to modify Chamness with setting the function to its minimal value. PHOSITA would have known about the uses of various manners to apply deviations and how to use them to modify Chamness. PHOSITA would have been motivated to do this as an application of a known technique to a known (device, method, or product) ready for improvement to yield predictable results (See MPEP § 2143 (I)(D)), specifically the use of standard deviations and data anchoring in modelling and analysis.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHAD A REVERMAN whose telephone number is (571)270-0079. The examiner can normally be reached Mon-Fri 9-5 EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kara Geisel can be reached at (571) 272-2416. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHAD ANDREW REVERMAN/Examiner, Art Unit 2877
/Kara E. Geisel/Supervisory Patent Examiner, Art Unit 2877
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