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 .
Information Disclosure Statement
IDS filed 4/17/2024 is being considered by the examiner
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 9 is rejected under 35 U.S.C. § 101 because the applicant has provided evidence that the applicant intends the term "machine-readable storage medium" to include non-statutory matter. The applicant describes a computer-readable storage medium as including open ended language and thus it is reasonable to interpret it to include all possible mediums, including non-statutory mediums (see paragraph [0023]). The words "storage" and/or "recording" are insufficient to convey only statutory embodiments to one of ordinary skill in the art absent an explicit and deliberate limiting definition or clear differentiation between storage media and transitory media in the disclosure. As such, the claim(s) is/are drawn to a form of energy. Energy is not one of the four categories of invention and therefore, this/these claim(s) is/are not statutory. Energy is not a series of steps or acts and thus is not a process. Energy is not a physical article or object and as such is not a machine or manufacture. Energy is not a combination of substances and therefore not a composition of matter.
The Examiner suggests amending the claim to read as a "non-transitory machine-readable storage medium".
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1 recites the limitation "the measurement results" in line 7. There is insufficient antecedent basis for this limitation in the claim.
Claim 4 recites the limitation "the links" in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claim 10 recites the limitation "the cluster centers" in line 2. There is insufficient antecedent basis for this limitation in the claim.
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.
Claims 1, 2, and 5-10 are rejected under 35 U.S.C. 103 as being unpatentable over Kou et al. [US Pub. 2020/0050190] ("Kou").
With regard to claim 1, Kou teaches a method for adjusting a process controller in order to manufacture one or a plurality of components in production ("Feedback controller 400 produces process corrections (PC) 406 for multiple threads 404, and chooses the appropriate process correction PC for a current wafer … process corrections can be chosen and applied on a per-wafer basis, or they may be applied per lot [par. 0072]"), comprising:
(S1) obtaining input data characterizing the one or a plurality of components ("the term 'object data' as used in the introduction and claims encompasses a wide variety of data that may be gathered in the manufacturing facility, either for historic product units, or new product units to be processed. In particular, the term 'object data' as used in the introduction and claims encompasses both the performance data PDAT (measured from processed product units after processing and stored in storage 252) and the other types of object data ODAT (measured from product units or other systems before and/or during processing and stored in storage 260) [par. 0064]");
(S2) determining clusters in the input data ("a statistical analysis of the historic performance data PDAT is performed [par. 0073]" and "the results of the statistical analysis are applied to define a first partitioning of the product units represented in the historic performance data. This partitioning is based on the position of each product unit in a multidimensional space defined by the principal component vectors, within the multidimensional space defined by the set of performance parameters measured and represented in the performance data PDAT [par. 0075]" and "the partitioning of product units into different subsets or 'clusters', based on the results of the statistical analysis [par. 0076]");
(S3) grouping the components into the determined cluster based on their input data ("the partitioning of product units into different subsets or 'clusters', based on the results of the statistical analysis [par. 0076]")"); and
(S4) determining a parameterization of a specified process step for the one or plurality of components or subsequent components ("Feedback controller 400 produces process corrections (PC) 406 for multiple threads 404, and chooses the appropriate process correction PC for a current wafer … applied on future wafers [par. 0072]") ("These same context criteria are used in combination with the current wafer context data CTX, when choosing the process corrections to be applied on future wafers [par. 0072]").
Kou does not explicitly teach the above steps performed by way of a R2R controller; however, Kou does teach where the steps are performed by a module ("FIG. 4 is a flowchart of the method implemented by the statistical analysis module 270 and partition refining module 272 [par. 0072]") and also teaches where a run-to-run controller is used for various steps of the process [par. 0102, 0113] and "They may be deployed for example in a run-to-run controller, which can, either automatically or with user guidance, refine the grouping and selection criteria, as well as other aspects of the control system, during development and high volume manufacturing [par. 0134]". It would have been obvious to one having ordinary skill in the art at the time of filing the invention to have utilized a R2R controller in the process steps of Kou, for the benefit of efficiently adjusting parameters between wafer runs.
With regard to claim 2, Kou teaches the method according to claim 1, wherein:
a respective similarity between the clusters is determined in addition to the clusters ("the most representative wafers for each cluster and chuck are selected, based on their position within their cluster and/or with respect to the neighboring clusters [par. 0102]" and "where wafers are clustered along two curves 602, 604 by a mixed regression analysis, [waf]ers 630, 632 that lie on or close to the curve can be selected as representative samples for metrology, in preference to other wafers that belong to the relevant cluster, but are some distance from the curve in the parameter PRH that is plotted. The distance from the curve may be used as a score for ranking the wafers in this selection process. KPIs such as Silhouette value can be extended to clustering in a curve-based space, as well as clustering in the principle components [par. 0103]"),
a link between the clusters is determined depending on the determined similarities ("A regression analysis can be used to fit a logarithmic curve to the observed data in a well-known manner [par. 0081]"), and
the parameterization is determined additionally, depending on the links between the groups ("A reticle heating correction based on such regression analysis may be something that is applied as part of a feedforward control system [par. 0083]" and "Feedback controller 400 produces process corrections (PC) 406 for multiple threads 404, and chooses the appropriate process correction PC for a current wafer … applied on future wafers [par. 0072]").
Because Kou teaches, "various statistical measures can be applied to identify a desired number of most representative product units [par. 0102]" and "FIG. 6 illustrates another example of the type of statistical analysis that might be applied, in particular a mixed regression analysis [par. 0080]," it would have been obvious to one having ordinary skill in the art at the time of filing the invention to have utilized various analysis when determining appropriate process correction, for the benefit of making better informed corrections.
With regard to claim 5, Kou teaches the method according to claim 1, wherein:
given a similarity between two clusters greater than a specified threshold value, combining these two clusters ("Boundaries for the exclusion of excursion wafers can be defined in the multi-dimensional space, or in a single dimension, if desired. The boundaries can be defined entirely automatically and/or with expert assistance, and may have arbitrary shape in the multi-dimensional space defined by the statistical analysis. For example, tight boundaries may surround individual clusters, or one boundary may encompass the entire set. The boundaries can be refined as volume manufacturing progresses, and may be set wider in a development phase [par. 0100];" it would have been obvious to one having ordinary skill in the art at the time of filing the invention to have refined the boundary to encompass multiple clusters, because in having done so would have predictably grouped wafers according to known methods).
With regard to claim 6, Kou teaches the method according to claim 1, wherein:
performing steps S1 to S4 again at specified times or upon the occurrence of a specified event, and subsequently checking whether the R2R controller should be reset and/or whether a current grouping should be replaced by the new grouping from step S3 ("wherein the plurality of product units is one subset of a set of product units being subjected to said industrial process, the method comprising as a preliminary step partitioning the set of product units into a plurality of subsets, the steps (a) and (b) of the method being performed separately for each subset [par. 0158]" and "wherein in step (c) different corrections are defined for use in controlling processing of the different subsets of the set of product units, the different corrections being based on the metrology results of the selected sample product units for the corresponding subset [par. 0159];" where the grouping is replaced for each subset).
Note: claim is presented in the alternative.
With regard to claim 7, Kou teaches an apparatus which is configured to perform the method according to claim 1 ("a control system is disclosed as an example in which the techniques of the present disclosure may be employed [par. 0071]").
With regard to claim 8, Kou teaches a computer program comprising instructions which, when the program is executed by a computer, prompt the latter to perform the method according to claim 1 ("The invention further provides a computer program product comprising machine readable instructions for causing a general purpose data processing apparatus to implement all or part of a method and control apparatus as set forth above [par. 0023]").
With regard to claim 9, Kou teaches a machine-readable storage medium on which the computer program according to claim 8 is stored ("The invention further provides a computer program product comprising machine readable instructions for causing a general purpose data processing apparatus to implement all or part of a method and control apparatus as set forth above [par. 0023]").
With regard to claim 10, Kou teaches the method according to claim 1, wherein:
a respective similarity between the cluster centers is determined in addition to the clusters ("the most representative wafers for each cluster and chuck are selected, based on their position within their cluster and/or with respect to the neighboring clusters [par. 0102]" and "where wafers are clustered along two curves 602, 604 by a mixed regression analysis, [waf]ers 630, 632 that lie on or close to the curve can be selected as representative samples for metrology, in preference to other wafers that belong to the relevant cluster, but are some distance from the curve in the parameter PRH that is plotted. The distance from the curve may be used as a score for ranking the wafers in this selection process. KPIs such as Silhouette value can be extended to clustering in a curve-based space, as well as clustering in the principle components [par. 0103]"),
a link between the clusters is determined depending on the determined similarities ("A regression analysis can be used to fit a logarithmic curve to the observed data in a well-known manner [par. 0081]"), and
the parameterization is determined additionally, depending on the links between the groups ("A reticle heating correction based on such regression analysis may be something that is applied as part of a feedforward control system [par. 0083]" and "Feedback controller 400 produces process corrections (PC) 406 for multiple threads 404, and chooses the appropriate process correction PC for a current wafer … applied on future wafers [par. 0072]").
Because Kou teaches, "various statistical measures can be applied to identify a desired number of most representative product units [par. 0102]" and "FIG. 6 illustrates another example of the type of statistical analysis that might be applied, in particular a mixed regression analysis [par. 0080]," it would have been obvious to one having ordinary skill in the art at the time of filing the invention to have utilized various analysis when determining appropriate process correction, for the benefit of making better informed corrections.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Kou in view of Beckman et al. [US Pub. 2018/0285453] ("Beckman").
With regard to claim 3, Kou teaches the method according to claim 2. Kou does not explicitly teach wherein the similarities between the clusters are determined based on a distance dimension and/or a correlation between the respective clusters.
In the same field of endeavor (clustering data), Beckman teaches wherein similarities between clusters are determined based on a distance dimension and/or a correlation between the respective clusters ("indicate how similar multiple document clusters are to each other. In a particular embodiment, the electronic device 210 may display a first cluster as the 'center' or 'target' cluster, and may display at least two additional clusters a distance away from the first cluster, where the respective distances between the additional clusters and the center cluster may be indicative of the similarity between the respective additional cluster and the center cluster (i.e., the closer the distance, the more similar the clusters) [par. 0036]").
Because Kou teaches, "Boundaries for the exclusion of excursion wafers can be defined in the multi-dimensional space, or in a single dimension, if desired. The boundaries can be defined entirely automatically and/or with expert assistance, and may have arbitrary shape in the multi-dimensional space defined by the statistical analysis. For example, tight boundaries may surround individual clusters, or one boundary may encompass the entire set. The boundaries can be refined as volume manufacturing progresses, and may be set wider in a development phase [par. 0100]," it would have been obvious to one having ordinary skill in the art at the time of filing the invention to have included Beckman's teachings of distance between clusters, with the teachings of Kou, for the benefit of determining similarities between clusters in order to refine set boundaries.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Kou in view of Liu et al. [US Pub. 2023/0222360] ("Liu").
With regard to claim 4, Kou teaches the method according to claim 1. Although Kou teaches the parameterization is determined depending on links ("A reticle heating correction based on such regression analysis may be something that is applied as part of a feedforward control system [par. 0083]" and "Feedback controller 400 produces process corrections (PC) 406 for multiple threads 404, and chooses the appropriate process correction PC for a current wafer … applied on future wafers [par. 0072]." Because Kou teaches, "various statistical measures can be applied to identify a desired number of most representative product units [par. 0102]" and "FIG. 6 illustrates another example of the type of statistical analysis that might be applied, in particular a mixed regression analysis [par. 0080]," it would have been obvious to one having ordinary skill in the art at the time of filing the invention to have utilized various analysis when determining appropriate process correction, for the benefit of making better informed corrections).
Kou does not explicitly teach wherein: the links are combined into a link matrix, the entries of the matrix are normalized, and the parameterization is determined depending on the link matrix.
In the same field of endeavor (determining similarities between data sets), Liu teaches wherein: links are combined into a link matrix ("cluster C1 includes 5 samples from the circle dataset and 11 samples from the square dataset. Cluster 2 includes 13 samples from the circle dataset and 7 samples from the square dataset. The diagram 506 can illustrate how the CSD 202 uses the clustering data to arrive at a CSS. The CSD 202 can build a cluster matrix Mij based on clustering data of clusters C1 and C2 [par. 0041]"), the entries of the matrix are normalized ("the size of a dataset from one source can be disproportionately larger than the other datasets in the combined dataset. If individual source scores or CSS are derived using raw number of samples, they can be unduly influenced by the larger dataset. In those instances, a normalization can remove the bias introduced by the size of the datasets [par. 0043]").
It would have been obvious to one having ordinary skill in the art at the time of filing the invention to have included Liu's teachings of a matrix and normalizing the matrix, with the teachings of Kou, for the benefit of removing biases in obtained data sets.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chan et al. [US Pub. 2013/0011939] teaches a method for processing a plurality of semiconductor wafers includes acquiring a process parameter measurement for each of the semiconductor wafers, associating each of the semiconductor wafers with one of a plurality of groups based on a respective process parameter measurement for each of the semiconductor wafers, where each respective group corresponds to a respective recipe, and for each one of the groups, processing ones of the semiconductor wafers associated with that group together according to a respective recipe.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VINCENT W CHANG whose telephone number is (571)270-1214. The examiner can normally be reached (M-F) 10:00 am - 6:00 pm.
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, Mohammad Ali can be reached at 571-272-4105. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/VINCENT WEN-LIANG CHANG/
Examiner
Art Unit 2119
/ZIAUL KARIM/Primary Examiner, Art Unit 2119
Prosecution Insights