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 .
Election/Restrictions
Applicant’s election without traverse of Group II in the reply filed on 11/25/25 is acknowledged.
Drawings
The drawings filed on 8/16/23 are accepted by the examiner.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 1/9/24 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claims 30-33 and 35-48 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. The claim(s) recite(s) mental steps involving selecting components to be measured from a plurality of components, wherein the selection is made according to at least one selection parameter, determining at least one production parameter, and adapting at least one selection parameter based on at least one of the production parameter or a change in the production parameter, wherein: the adaptation is implemented with a time offset, and the adaptation is implemented at a time at which the component produced using the production parameter is measured, creating component-specific measurement data by evaluation of the measurement data, wherein the adaptation of the at least one selection parameter is additionally implemented based on a result of the evaluation, wherein the selection parameter is a sampling frequency, determining at least one measurement parameter, wherein the adaptation of the at least one selection parameter is additionally implemented based on the measurement parameter or a change in the measurement parameter, wherein the at least one measurement parameter represents a parameter associated with a measurement sensor, wherein the adaptation of the at least one selection parameter is additionally implemented based on a set of rules, wherein the at least one production parameter represents at least one of.an ambient condition, a production tool, a production method, a number of components produced since a particular time, a production duration since a particular time, a number of batches produced since a particular time, or a shift group, wherein the at least one selection parameter is at least one of (i) a sampling frequency or (ii) an ordinal number in a sequence of produced components, wherein: a first selection parameter of the at least one selection parameter is a sampling frequency, and a second selection parameter of the at least one selection parameter is an ordinal number in a sequence of produced components, after adapting the at least selection parameter, selecting additional components to be measured from a second plurality of components, wherein the selection is made according to the at least one adapted selection parameter, determining the set of rules, wherein: at least one quality measure is determined by the evaluation of the measurement data, and the adaptation of the at least one selection parameter is additionally implemented based on the quality measure or a change in the quality measure, at least one component-specific property is determined by the evaluation of the measurement data, and at least one of: the adaptation of the at least one selection parameter is carried out in response to at least one of: the at least one component-specific property for a predetermined number of measured components differing from a target value by more or less than a predetermined amount, wherein adapting the at least one selection parameter based on the production parameter or a change in the production parameter includes changing the at least one selection parameter based on the production parameter or a change in the production parameter, adapting the at least one selection parameter is only based on the production parameter or a change in the production parameter; after adapting the at least selection parameter, selecting additional components to be measured from a second plurality of components, wherein the selection is made according to the at least one adapted selection parameter; creating component-specific measurement data by evaluation of the measurement data; and further adapting the at least adapted selection parameter based on a result of the evaluation (claims 30-33, 35-37, and 39-48), these limitations are recited in high level of generality constitutes as a mental process, such as an evaluation or judgement, that can be performed in the human mind.
This judicial exception is not integrated into a practical application because the additional limitations of measuring selected components using a coordinate measuring machine, at least one coordinate measuring machine, measuring selected additional components using a coordinate measuring machine (claims 31, 35 and 48) represent mere data collection which is an insignificant extrasolution activity. The non-transitory computer-readable medium and at least one evaluation and control device (claims 33 and 35) are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications that they represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014). Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system (Alice Corp. Pty. Ltd. v. CLS Bank Int’l 573 U.S. __, 134 S. Ct. 2347, 110 U.S.P.Q.2d 1976 (2014)). Accordingly, these additional element does not integrate the abstract idea into a practical application. The limitation of automating the adaptation of the selection parameter (claim 38) and using machine learning to determine the set of rules (claim 40) provide nothing more than mere instructions to implement an abstract idea on a generic computer, see MPEP2106.05(f).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the insignificant extra-solution activity of data collection is considered well-understood, routine, and conventional, see mpep 2106.05(d), infra applied prior art, references cited. The non-transitory computer-readable medium and at least one evaluation and control device are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications, which cannot provide an inventive concept. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system (Alice Corp. Pty. Ltd. v. CLS Bank Int’l 573 U.S. __, 134 S. Ct. 2347, 110 U.S.P.Q.2d 1976 (2014)). The additional elements of automating the adaptation of the selection parameter and determining the set of rules using machine learning, are at best, mere instructions to “apply” the abstract ideas, which cannot provide an inventive concept, and is considered well-understood, routine, and conventional, see MPEP2106.05(f).
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 33 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 33 recites non-transitory computer-readable medium comprising instructions to perform various steps (selecting, determining, adapting, etc.), it is not clear how a non-transitory computer-readable medium comprising instructions by itself can perform these steps. Therefore, claim 33 is unclear and indefinite, the examiner suggested to amend the claim to recite “a non-transitory computer-readable medium comprising instructions, when executed by a processor, cause the processor to…” to overcome the rejection.
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.
Claim(s) 30-33, 35-39, 41-42, and 44-47 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US7698012 to Shanmugasundramet al. (hereinafter “Shanmugasundram”).
As for claim 30, Shanmugasundram discloses a method for measuring components produced by a production device (Shanmugasundram, see col. 3 lines 16-31), the method comprising:
selecting components to be measured from a plurality of components, the selection is made according to at least one selection parameter (Shanmugasundram, see col. 3 lines 16-31 and col. 5 line 46-col. 6 line 2),
determining at least one production parameter (Shanmugasundram, see col. 3 lines 16-31 and col. 5 line 46-col. 6 line 2, it is noted that detecting a change in a control parameter in the manufacturing process can be interpreted as determining at least one production parameter (i.e. by detecting a change in a control parameter, the production parameter is determined as changed), and
adapting at least one selection parameter based on the production parameter (Shanmugasundram, see col. 3 lines 16-35 and col. 5 line 46-col. 6 line 2), wherein:
the adaptation is implemented with a time offset, and the adaption is implemented at a time at which the component produced using the production parameter is measured (Shanmugasundram, see Fig. 1 steps 113-115, col. 3 lines 16-35 and col. 7 lines 59-67, it is noted that the measurement of the wafer according to the adjusted sampling plan is performed after the change of recipe is detected (i.e. the selection adaptation is implemented with a delay (after the detection of the change) and the selection parameter is adapted is implemented at a time a time at which the wafer (component) produced using the production parameter is measured).
Claim 33 is a non-transitory computer-readable medium claim corresponding to the method claim, it is therefore rejected under similar reasons set forth in the rejection of claim 1, Shanmugasundram further discloses a non-transitory computer-readable medium (Shanmugasundram, see col. 2 lines 27-30).
Claim 35 is a system claim corresponding to the method claim, it is therefore rejected under similar reasons set forth in the rejection of claim 1, Shanmugasundram further discloses at least one coordinate measuring machine (Shanmugasundram, see col. 3 lines 16-35 and col. 4 lines 53-55, it is noted that a wafer metrology tool measures coordinate and therefore it could be interpreted as a coordinate measuring machine); and at least one evaluation and control device, wherein the system is configured to carry out a measurement method (Shanmugasundram, see Fig. 6 and col. 12 lines 22-35).
As per claim 31, the rejection of claim 30 is incorporated, Shanmugasundram further discloses creating component-specific measurement data by measuring selected components using a coordinate measuring machine and an evaluation of the measurement data (Shanmugasundram, see col. 3 lines 16-35 and col. 4 lines 53-55, it is noted that a wafer metrology tool measures coordinate and therefore it could be interpreted as a coordinate measuring machine);
wherein the adaptation of the at least one selection parameter is additionally implemented based on a result of the evaluation (Shanmugasundram, see col. 3 lines 16-35).
As per claim 32, the rejection of claim 30 is incorporated, Shanmugasundram further discloses the selection parameter is a sampling frequency (Shanmugasundram, see col. 5 lines 61-67).
As per claim 36, the rejection of claim 30 is incorporated, Shanmugasundram further discloses determining at least one measurement parameter, wherein the adaptation of the at least one selection parameter is additionally implemented based on the measurement parameter (Shanmugasundram, see col. 4 lines 53-59).
As per claim 37, the rejection of claim 36 is incorporated, Shanmugasundram further discloses wherein the at least one measurement parameter represents a parameter associated with a measurement sensor (Shanmugasundram, see col. 4 lines 53-55 and col. 7 lines 52-55).
As per claim 38, the rejection of claim 30 is incorporated, Shanmugasundram further discloses the adaptation of the at least one selection parameter is performed in a manner that is at least partially automated (Shanmugasundram, see col. 3 lines 16-35 and col. 6 lines 9-12).
As per claim 39, the rejection of claim 30 is incorporated, Shanmugasundram further discloses the adaptation of the at least one selection parameter is additionally implemented based on a set of rules (Shanmugasundram, see Fig. 1).
As per claim 41, the rejection of claim 30 is incorporated, Shanmugasundram further discloses the at least one production parameter represents a production method (Shanmugasundram, see col. 3 lines 16-35 and col. 5 line 63-col. 6 line 2, it is noted that the recipe can be interpreted as a production method).
As per claim 42, the rejection of claim 30 is incorporated, Shanmugasundram further discloses the at least one selection parameter is a sampling frequency (Shanmugasundram, see col. 5 lines 61-67).
As per claim 44, the rejection of claim 30 is incorporated, Shanmugasundram further discloses after adapting the at least selection parameter, selecting additional components to be measured from a second plurality of components, wherein the selection is made according to the at least one adapted selection parameter (Shanmugasundram, see col. 3 lines 16-35 and col. 9 lines 32-48).
As per claim 45, the rejection of claim 31 is incorporated, Shanmugasundram further discloses at least one quality measure is determined by the evaluation of the measurement data and the adaption of the at least one selection parameter is additionally implemented based on the quality measure (Shanmugasundram, see col. 3 lines 16-35).
As per claim 46, the rejection of claim 31 is incorporated, Shanmugasundram further discloses at least one component-specific property is determined by the evaluation of the measurement data and the adaptation of the at least one selection parameter is carried out in response to the at least one component-specific property for a predetermined number of measured component differing from a target value by more or less than a predetermined amount (Shanmugasundram, see col. 8 line 62-col. 9 line 5).
As per claim 47, the rejection of claim 30 is incorporated, Shanmugasundram further discloses changing the at least one selection parameter to a value that is based on the production parameter (Shanmugasundram, see col. 3 lines 16-35).
Claim Rejections - 35 USC § 103
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:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 40 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shanmugasundram, in view of US20160349736 to Cheng et al. (hereinafter “Cheng”).
As per claim 40, the rejection of claim 39 is incorporated, Shanmugasundram does not explicitly disclose determining the set of rules using machine learning. However, Cheng in an analogous art discloses determining the set of rules using machine learning (Cheng, see [0032]-[0041]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Cheng into the method of Shanmugasundram. The modification would be obvious because one of the ordinary skill in the art would want to efficiently lower the sampling rate without worrying to skip the measurement of the abnormal workpiece that ought to be measured by adjusting the sampling rate using machine learning (Cheng, see [0032]-[0041] and [0126]).
Claim(s) 43 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shanmugasundram, in view of US5859964 to Wang et al. (hereinafter “Wang”).
As per claim 43, the rejection of claim 30 is incorporated, Shanmugasundram further discloses a first selection parameter of the at least one selection parameter is a sampling frequency (Shanmugasundram, see col. 5 lines 61-67). Shanmugasundram does not explicitly disclose a second selection parameter of the at least one selection parameter is an ordinal number in a sequence of produced components.
However, Wang in an analogous art discloses a second selection parameter of the at least one selection parameter is an ordinal number in a sequence of produced components (Wang, see col. 12 line 66-col. 13 line 11).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Wang into the method of Shanmugasundram. The modification would be obvious because one of the ordinary skill in the art would want to provide a method that allow different process models to be employed which best model the particular process being performed (Wang, see col. 3 lines 1-3).
Allowable Subject Matter
Claim 48 would be allowable if the rejection(s) under 35 U.S.C. 101, set forth in this Office action, is overcome and to include all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
US20200027008 discloses systems, articles of manufacture and apparatus to control data acquisition settings in edge-based deployments are disclosed. An example apparatus includes a model generator to transform sensor data to variance data, and differentiate the variance data to generate variance rate of change data. The example apparatus also includes a model analyzer to determine subsets of the variance rate of change data associated with respective data acquisition settings, determine a count of data points corresponding to the rate of change data, and determine an interval spacing value based on the count of the data points and a number of subsets of the variance rate of change data. The example apparatus also includes a solution identifier to calculate candidate solutions at respective ones of the data points corresponding to the interval spacing value, respective ones of the candidate solutions corresponding to respective data acquisition settings of a data acquisition system, and select one of the candidate solutions satisfying an operational threshold of the data acquisition system.
US20070025485 discloses an arbitrary metric stream is processed initially at an interim sampling rate to derive a plurality of samples. The samples are analyzed preferably to determine an estimate of the effective bandwidth of the metric stream. As a result of the analysis, an improved sampling rate is determined and adopted for further sampling. In a preferred embodiment, the improved sampling rate is a function of the effective bandwidth.
US10250463 discloses a method for online monitoring of a physical environment using a variable data sampling rate is implemented by a computing device. The method includes sampling, at the computing device, at least one data set using at least one sampling rate. The method also includes processing the at least one data set with condition assessment rules. The method further includes determining whether the at least one data set indicates a change in state of the physical environment. The method additionally includes updating the at least one sampling rate.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JASON LIN whose telephone number is (571)270-3175. The examiner can normally be reached on Monday-Friday 9:30 a.m. – 6:00 p.m. PST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert E. Fennema can be reached on (571)272-2748. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JASON LIN/
Primary Examiner, Art Unit 2117