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 .
The Office Action is in response to the application filed on 09/25/2023. Claims 1-8, 12-13, 15, 17-19,
23-24, and 26-29 are pending in the application. Claims 1, 23, 24, and 26 are independent claims.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because reference
character “S410” has been used to designate both “test pattern” and “resist process parameter,” and reference character “S420” has been used to designate both “exposure process parameter” and “development process parameter” in the FIG.4. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The abstract dated 09/25/2023 has been reviewed. It has 150 words and 10 lines and no legal
phraseology. It is accepted.
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.
Claims 1-8, 12-13, 15, 17-19, 23-24, and 26-29 are 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 1 recites “… the process model is constructed based on actual process data generated in an actual manufacturing process of the display panel, and the measurement model is constructed based on actual process data and actual measurement data …,” which is indefinite because it is unclear if the later recited “actual process data” refers to the same actual process data used to construct the process model or to different actual process data. For the purposes of examination, it interpreted as “… the process model is constructed based on actual process data generated in an actual manufacturing process of the display panel, and the measurement model is constructed based on the actual process data and actual measurement data …”
Claim 3 recites the limitation "the feature data output by the process model …" in line 11. There is insufficient antecedent basis for this limitation in the claim.
Claim 4 recites the limitation "the feature data output by the process model," in line 6. There is insufficient antecedent basis for this limitation in the claim.
Claim 8 recites “wherein the doomsday weighted algorithm comprises calculating … wherein the linear weighted algorithm comprises calculating … wherein the trapezoidal weighted algorithm comprises calculating … wherein the square coefficient weighted algorithm comprises calculating …” which is indefinite because claim 7 recites that the weighted moving average algorithm comprises “one of” four different algorithms. Claim 8 then recites limitations directed to each of the four different algorithms without specifying whether the four algorithms are required collectively or alternatively. For the purposes of examination, it interpreted as “… wherein the trapezoidal weighted algorithm comprises calculating … where each of C1, C2, ... Cn is a value of the process parameter of a respective cycle, and n is an integer greater than 1; or wherein the square coefficient weighted algorithm comprises calculating …”
Claim 17 recites the limitation "the development parameter" in line 7. There is insufficient antecedent basis for this limitation in the claim.
Claim 26 recites “in the digital processing process, the method of claim 1 is performed by using a process model and a measurement model which are generated based on the actual process data and the actual measurement data …,” which is indefinite because it is unclear if “a process model and a measurement model” refer to the process model and measurement model recited in claim 1 or additional process and measurement models. For the purposes of examination, the examiner interprets this limitation as requiring the entire method of claim 1 to be performed in the digital processing process, and interprets “a process model and a measurement model” recited in claim 26 as referring to the same process model and measurement model recited in claim 1. The examiner further interprets the actual process data and actual measurement data obtained in the physical manufacturing process as the data used to generate the process model and measurement model as recited in claim 26, which are interpreted as the same models recited in claim 1.
Claim 28 recites the limitation " the loading process data operation" in line 2. There is insufficient antecedent basis for this limitation in the claim.
The remaining claims are dependent upon, or incorporate, one of the claims listed above and are rejected for the same reason.
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.
The claims 1-8, 12-13, 15, 17-19, 23-24, and 26-29 are rejected under 35 USC § 101 because the
claimed invention is directed to judicial exception, an abstract idea, it has not been integrated into practical application, and the claims further do not recite significantly more than the judicial exception. Examiner has evaluated the claims under the framework provided in the 2019 Revised Patent Subject Matter Eligibility Guidance published in the Federal Register 01/07/2019, as well as subsequent USPTO eligibility guidance updates, and has provided such analysis below.
Step 1: Are the claims to a process, machine, article of manufacture or composition of matter?"
Yes, Claims 1-8, 12-13, 15, 17-19 are directed to method and fall within the statutory category of process;
Yes, Claim 23 is directed to device and falls within the statutory category of machine;
Yes, Claim 24 is directed to non-transitory computer readable storage medium and falls within the statutory category of article of manufacture;
Yes, Claims 26-29 are directed to method and fall within the statutory category of process.
In order to evaluate the Step 2A inquiry "Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?" we must determine, at Step 2A Prong 1, whether the claim recites a law of nature, a natural phenomenon or an abstract idea and further whether the claim recites additional elements that integrate the judicial exception into a practical application.
Step 2A Prong 1:
Mental Processes:
As explained in MPEP 2106.04(a)(2)(III): Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer").
Further, as explained in MPEP 2106.04(a)(2)(III)(A): In contrast, claims do recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. Examples of claims that recite mental processes include:
• a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016);
• claims to "comparing BRCA sequences and determining the existence of alterations," where the claims cover any way of comparing BRCA sequences such that the comparison steps can practically be performed in the human mind, University of Utah Research Foundation v. Ambry Genetics, 774 F.3d 755, 763, 113 USPQ2d 1241, 1246 (Fed. Cir. 2014);
• a claim to collecting and comparing known information (claim 1), which are steps that can be practically performed in the human mind, Classen Immunotherapies, Inc. v. Biogen IDEC, 659 F.3d 1057, 1067, 100 USPQ2d 1492, 1500 (Fed. Cir. 2011); and
• a claim to identifying head shape and applying hair designs, which is a process that can be practically performed in the human mind, In re Brown, 645 Fed. App'x 1014, 1016-17 (Fed. Cir. 2016) (non-precedential).
Further, as explained in MPEP 2106.04(a)(2)(III)(C): 1. Performing a mental process on a generic computer. An example of a case identifying a mental process performed on a generic computer as an abstract idea is Voter Verified, Inc. v. Election Systems & Software, LLC, 887 F.3d 1376, 1385, 126 USPQ2d 1498, 1504 (Fed. Cir. 2018) … 2. Performing a mental process in a computer environment. An example of a case identifying a mental process performed in a computer environment as an abstract idea is Symantec Corp., 838 F.3d at 1316-18, 120 USPQ2d at 1360 … 3. Using a computer as a tool to perform a mental process. An example of a case in which a computer was used as a tool to perform a mental process is Mortgage Grader, 811 F.3d. at 1324, 117 USPQ2d at 1699.
Claim 1: The limitations of “generating, based on design data of a process of the display panel, simulation process data for performing the process,” as drafted, is process that, but for the recitation of generic computing components, under the broadest reasonable interpretation (BRI) in light of the specification, covers performance of the limitation in the human mind.
For example, a person is capable of observing/reviewing design information for a display panel process and, based on the design requirements, selecting or determining candidate process parameters to be evaluated. The steps include observation, evaluation, judgment, and reasoning processes that can be performed mentally or with the aid of pen and paper (The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011).).
Examiner note: The claimed limitation is broadly recited and does not require any particular implementations or degree of processing complexity beyond human evaluation and judgement that would prevent the limitation from being performed in the human mind. See MPEP 2106.04(a)(2)(III).
Claim 1: The limitations of “performing, by using a process model, a simulation of performing the process based on the simulation process data; and
verifying, by using a measurement model, whether the simulation process data is applicable to actual production based on the simulation,
wherein the process model is constructed based on actual process data generated in an actual manufacturing process of the display panel, and the measurement model is constructed based on actual process data and actual measurement data which are generated in the actual manufacturing process of the display panel,” as drafted, is process that, but for the recitation of generic computing components, under the broadest reasonable interpretation (BRI) in light of the specification, covers performance of the limitation in the human mind.
For example, a person is capable of considering the candidate process parameters and a known relationship derived from prior actual process data to estimate a process result, and further considering the estimated process result together with an evaluation relationship derived from prior actual process data and actual measurement information to judge whether the candidate process parameters are suitable for actual production. The steps include observation, evaluation, judgment, and reasoning processes that can be performed mentally or with the aid of pen and paper (The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011).).
Examiner note: The claimed limitations are broadly recited and does not require any particular complexity, specific computer implementation, or algorithmic processing beyond human evaluation and judgment that would prevent the limitations from being performed in the human mind. See MPEP 2106.04(a)(2)(III).
In addition, as explained in MPEP 2106.04(II)(B): A claim may recite multiple judicial exceptions. For example, claim 4 at issue in Bilski v. Kappos, 561 U.S. 593, 95 USPQ2d 1001 (2010) recited two abstract ideas, and the claims at issue in Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 101 USPQ2d 1961 (2012) recited two laws of nature. However, these claims were analyzed by the Supreme Court in the same manner as claims reciting a single judicial exception, such as those in Alice Corp., 573 U.S. 208, 110 USPQ2d 1976.
Mathematical Concepts:
As explained in MPEP 2106.4(a)(2)(I): “The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. It is important to note that a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989). See, e.g., SAP America, Inc. v. InvestPic, LLC, 898 F.3d 1161, 1163, 127 USPQ2d 1597, 1599 (Fed. Cir. 2018) (holding that claims to a “series of mathematical calculations based on selected information” are directed to abstract ideas); Digitech Image Techs., LLC v. Elecs. for Imaging, Inc., 758 F.3d 1344, 1350, 111 USPQ2d 1717, 1721 (Fed. Cir. 2014) (holding that claims to a “process of organizing information through mathematical correlations” are directed to an abstract idea); and Bancorp Servs., LLC v. Sun Life Assurance Co. of Can. (U.S.), 687 F.3d 1266, 1280, 103 USPQ2d 1425, 1434 (Fed. Cir. 2012) (identifying the concept of “managing a stable value protected life insurance policy by performing calculations and manipulating the results” as an abstract idea).
Further, as explained in MPEP 2106.04(a)(2)(I)(A): “A mathematical relationship is a relationship between variables or numbers. A mathematical relationship may be expressed in words or using mathematical symbols.”
Further, as explained in MPEP 2106.04(a)(2)(I)(C)recites: “For example, a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation.
Claim 1: The limitations of “performing, by using a process model, a simulation of performing the process based on the simulation process data,” under its broadest reasonable interpretation (BRI) in light of specification, recites a mathematical concept, including a mathematical relationship, formula or equation, calculation. In particular, the specification explains in paragraph [0061] that performing the process based on the simulation process data may be simulated based on a mathematical model, paragraph [0062] explains that the mathematical model may include the claimed process model. Paragraph [0064] further explains that the process model performs the simulation by establishing a linear or nonlinear relationship between the input and output, and that a mathematical formula may be established to identify the relationship between the input and output. Accordingly, under the BRI in light of the specification, the claimed simulation using the process model encompasses applying a mathematical relationship or formula to the simulation process data to determine a corresponding process result. Thus, the limitation recites a mathematical concept. See MPEP 2106.04(a)(2)(I).
Claims 23-24, and 26 recite the similar elements as claim 1, and are rejected for the same reasons under 35 U.S.C. 101.
Therefore, claims 1, 23-24, and 26 recite judicial exceptions. The claims have been identified to recite judicial exceptions, Step 2A Prong 2 will evaluate whether the claims are directed to the judicial exception.
Step 2A Prong 2: Claims 1, 23-24, and 26: The judicial exception is not integrated into a practical application.
The additional limitation of claims 23 and 24: "An electronic device, comprising a memory and a processor, wherein the memory stores instructions executable by the processor, and the instructions, when executed by the processor, cause the processor to implement …” and “A non-transitory computer readable storage medium storing computer instructions, wherein the computer instructions are configured to cause a computer to implement …” which are merely recitations of instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to implement the judicial exception, which does not integrate judicial exception into a practical application (see MPEP §2106.05(f)).
Further, the additional limitation of clam 26: “in the physical manufacturing process, at least one process of the display panel is performed, so as to obtain actual process data and actual measurement data,” which is merely an recitation of insignificant extra-solution activity, such as data gathering, i.e., obtaining actual process data and actual measurement data for use in the subsequent digital processing process, which does not integrate a judicial exception into practical application (see MPEP § 2106.05(g)). Examiner note: The additional limitation recites the physical manufacturing process only at a high level and does not require any particular manner of physical manufacturing process, or any particular technological operation.
Therefore, "Do the claims recite additional elements that integrate the judicial exception into a practical application? No, these additional elements do not integrate the abstract idea into a practical application, and they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
After having evaluated the inquiries set forth in Steps 2A Prong 1 and 2, it has been concluded that claims 1, 23-24, and 26 are not only recite a judicial exception but that the claims are directed to the judicial exception as the judicial exception has not been integrated into practical application.
Step 2B: Claims 1, 23-24, and 26: The claim does not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than generic computing components to the judicial exception and an recitation of insignificant extra-solution activity, which do not amount to significantly more than the abstract idea.
As explained in MPEP 2106.05(A), “Limitations that the courts have found not to be enough to qualify as "significantly more" when recited in a claim with a judicial exception include:
i. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984 (see MPEP § 2106.05(f));
ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d));
iii. Adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea such as a step of obtaining information about credit card transactions so that the information can be analyzed by an abstract mental process, as discussed in CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011) (see MPEP § 2106.05(g));
iv. Generally linking the use of the judicial exception to a particular technological environment or field of use, e.g., a claim describing how the abstract idea of hedging could be used in the commodities and energy markets, as discussed in Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1010 (2010) or a claim limiting the use of a mathematical formula to the petrochemical and oil-refining fields, as discussed in Parker v. Flook, 437 U.S. 584, 588-90, 198 USPQ 193, 197-98 (1978) (MPEP § 2106.05(h)).”
As explained in MPEP 2106.05(d)(II), “The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, …; ii. Performing repetitive calculations, …; iii. Electronic recordkeeping, … (updating an activity log); iv. Storing and retrieving information in memory, …”
In particular, the additional limitations of claims 1, 23-24 and 26, when considered individually and in combination, do not amount to significantly more than the judicial exception. The claims do not recite a particular unconventional arrangement or additional functionality that amounts to significantly more than the judicial expectation.
Therefore, "Do the claims recite additional elements that amount to significantly more than the judicial exception? No, these additional elements, alone or in combination, do not amount to significantly more than the judicial exception. Having concluded analysis within the provided framework, claims 1, 23-24, and 26 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Dependent claims 2-8, 12-13, 15, 17-19, and 27-29 are also similar rejected under same rationale as cited above wherein these claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. These claims are merely further elaborate the mental process itself (or mathematical operations) or providing additional definition of process which does not impose any meaningful limits on practicing the abstract idea. Claims 2-8, 12-13, 15, 17-19, and 27-29 are also rejected for incorporating the deficiency of their independent claims 1 and 26.
Claim 2 recites “The method of claim 1, wherein the performing, by using a process model, a simulation of performing the process based on the simulation process data comprises: determining, by using the process model, feature data of the display panel achievable by performing the process based on the simulation process data,” as drafted, is process that, but for the recitation of generic computing components, under the broadest reasonable interpretation (BRI) in light of the specification, covers performance of the limitation in the human mind.
For example, a person is capable of considering the candidate process parameters and a known relationship derived from prior actual process data to determine corresponding feature information of the display panel that would result from use of the candidate process parameters. The steps include observation, evaluation, judgment, and reasoning processes that can be performed mentally or with the aid of pen and paper (The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011).). See MPEP 2106.04(a)(2)(III). Therefore, the claim 2 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 3 recites “The method of claim 1, wherein the verifying, by using a measurement model, whether the simulation process data is applicable to actual production based on the simulation, comprises:
determining, among the actual process data, actual process data having a similarity higher than a preset similarity threshold with respect to the simulation process data, as similar process data by using the measurement model;
determining, among the actual measurement data, feature data of the display panel obtained by actually performing the process based on the similar process data, as actual feature data; and
determining that the simulation process data is applicable to actual production, in response to a difference between the actual feature data and the feature data output by the process model being less than a preset difference threshold,” as drafted, is process that, but for the recitation of generic computing components, under the broadest reasonable interpretation (BRI) in light of the specification, covers performance of the limitation in the human mind.
For example, a person is capable of comparing prior actual process data with the candidate process parameters to identify similar process data having a similarity greater than a predetermined threshold, identifying from prior measurement information the corresponding feature information obtained using the identified similar process data, and comparing the identified feature information with the process model result (i.e., simulated/calculated feature data) to determine whether the difference is less than a predetermined threshold to judge whether the candidate process parameters suitable for actual production. The steps include observation, evaluation, judgment, and reasoning processes that can be performed mentally or with the aid of pen and paper (The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011).). See MPEP 2106.04(a)(2)(III). Therefore, the claim 3 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 4 recites “The method of claim 1, further comprising: before verifying, by using the measurement model, whether the simulation process data is applicable to actual production based on the simulation:
calculating a process fluctuation by applying a feedback parameter algorithm to the actual process data by using a control model, and
applying the process fluctuation to the feature data output by the process model.”
This limitation merely further specifies calculation and application of a process fluctuation by requiring the process fluctuations to be calculated from actual process data using a feedback parameter algorithm and applied to the feature data. The recited calculation and application of a calculated value to data represents mathematical calculations and relationships. Thus, the limitation merely recites a mathematical concept. See MPEP 2106.04(a)(2)(I). Therefore, the claim 4 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 5 recites “The method of claim 4, wherein the feedback parameter algorithm comprises one of a moving average algorithm, a weighted moving average algorithm, or an exponential moving average algorithm.”
This limitation merely further specifies different types of feedback parameter algorithms refer to claim 4. It is merely an extension of mathematical concepts. See MPEP 2106.04(a)(2)(I). Therefore, the claim 5 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 6 recites “The method of claim 5, wherein the moving average algorithm comprises calculating an average value of process parameters of a plurality of consecutive cycles according to an equation:
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where each of C1, C2,...Cn is a value of the process parameter of a respective cycle, and n is an integer greater than 1.”
This limitation merely further specifies one type of feedback parameter algorithm refer to claims 4 and 5. It is merely an extension of mathematical concepts. See MPEP 2106.04(a)(2)(I). Therefore, the claim 6 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 7 recites “The method of claim 5, wherein the weighted moving average algorithm comprises one of a doomsday weighted algorithm, a linear weighted algorithm, a trapezoidal weighted algorithm, or a square coefficient weighted algorithm.”
This limitation merely further specifies different types of weighted moving average algorithm refer to claims 4 and 5. It is merely an extension of mathematical concepts. See MPEP 2106.04(a)(2)(I). Therefore, the claim 7 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 8 recites “The method of claim 7, wherein the doomsday weighted algorithm comprises calculating a weighted average value of process parameters of a plurality of consecutive cycles according to an equation:
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where each of C1, C2, ...Cn is a value of the process parameter of a respective cycle, and n is an integer greater than 1;
wherein the linear weighted algorithm comprises calculating a weighted average value of process parameters of a plurality of consecutive cycles according to an equation:
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where each of C1, C2, ... Cn is a value of the process parameter of a respective cycle, and n is an integer greater than 1;
wherein the trapezoidal weighted algorithm comprises calculating a weighted average value of process parameters of a plurality of consecutive cycles according to an equation:
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where each of C1, C2, ... Cn is a value of the process parameter of a respective cycle, and n is an integer greater than 1;
wherein the square coefficient weighted algorithm comprises calculating a weighted average value of process parameters of a plurality of consecutive cycles according to an equation:
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where each of C1, C2, ... Cn is a value of the process parameter of a respective cycle, and n is an integer greater than 1.”
This limitation merely further specifies each type of weighted moving average algorithm refer to claims 4, 5 and 7. It is merely an extension of mathematical concepts. See MPEP 2106.04(a)(2)(I). Therefore, the claim 8 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 12 recites “The method of claim 5, wherein the exponential moving average algorithm comprises calculating a weighted average value of process parameters of a plurality of consecutive cycles according to an equation:
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where each of C1, C2, ...Cn is a value of the process parameter of a respective cycle, n is an integer greater than 1, and a is a weighted index.”
integer greater than 1.”
This limitation merely further specifies a type of feedback parameter algorithm refers to claims 4 and 5. It is merely an extension of mathematical concepts. See MPEP 2106.04(a)(2)(I). Therefore, the claim 12 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 13 recites “The method of claim 1, wherein the process of the display panel comprises a backplane manufacturing process that includes a lithography process for forming a film layer, the design data comprises a design pattern of a mask, and the generating, based on design data of a process of the display panel, simulation process data for performing the process comprises at least one of:
simulating at least a part of the design pattern of the mask to obtain a test pattern;
generating an exposure process parameter based on a received exposure parameter setting information;
generating a resist process parameter based on a received resist parameter setting information; or
generating a development process parameter based on a received development parameter setting information.”
This limitation merely further specifies the display panel process as a backplane manufacturing process including a lithography process for forming a film layer, the design data as including a mask design pattern, and the generation of simulation process data as including determining a test pattern or process parameter based on corresponding design data or parameter setting information. It merely further specifies the mental process recited in claim 1, e.g., a person is capable of reviewing the mask design pattern to determine a corresponding test pattern, or considering the parameter setting information to determine an exposure, resist, or development process parameter. See MPEP 2106.04(a)(2)(III). Further, the limitation of a backplane manufacturing process including a lithography process for forming a film layer merely links the use of the identified mental process to a particular technological environment or field of use, and does not integrate the judicial exception into a practical application and amount to significantly more than the judicial exception. See MPEP § 2106.05(h). Therefore, the claim 13 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 15 recites “The method of claim 13, wherein:
the exposure process parameter comprises at least one of a numerical aperture, a wavelength, a coherence factor, an illumination type, an exposure magnification, and a focus position; and
the resist process parameter comprises at least one of a type of photoresist, a thickness and development rate of photoresist, a substrate material, or a concentration distribution of photosensitive compound (PAC).”
This limitation merely further specifies the exposure process parameter and resist process parameter generated in claim 13 by identifying particular types of exposure and resist parameters. It merely an extension of the metal process recited in claim 13, e.g., a person is capable of considering the corresponding parameter setting information to determine an exposure process parameter having at least one of exposure characteristics and a resist process parameter having at least of the resist characteristics. Therefore, the claim 15 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 17 recites “The method of claim 13, wherein the generating, based on design data of a process of the display panel, simulation process data for performing the process further comprises at least one of:
performing lens projection simulation on the test pattern based on the exposure process parameter to obtain aerial image data; or
generating graphic data of the film layer which has been developed, based on the development parameter.”
This limitation merely further specifies the generation of simulation process data recited in claim 13 as including performing a lens projection simulation based on the test pattern and exposure process parameter to obtain aerial image data, or generating graphic data of a developed film layer based on a development parameter. These limitations merely instruct performing the simulation and data generation functions at a high level of generality, without specifying a particular manner or mechanism for accomplishing result. Thus, the limitations merely use a computing system as a tool to implement the abstract idea, and do not integrate the judicial exception into a practical application and amount to significantly more than the judicial exception. See MPEP § 2106.05(f). Therefore, the claim 17 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 18 recites “The method of claim 17, further comprising:
presenting at least one of the aerial image data and the graphic data through a user interaction interface and receiving an input from a user, and
adjusting at least one of the exposure process parameter, the resist process parameter and the development process parameter based on the input from the user.”
This limitation merely further specifies presenting aerial image data or graphic data through a user interaction interface, receiving user input, and adjusting at least one process parameter based on the user input. The presenting and receiving limitations merely an recitation of insignificant extra-solution activity such as data gathering and data outputting, i.e., displaying data and obtaining input from user. See MPEP § 2106.05(g). The adjusting limitation merely uses a computer as a tool to perform identified abstract idea. See MPEP § 2106.05(f). Thus, the limitations do not integrate the judicial exception into a practical application and amount to significantly more than the judicial exception. Therefore, the claim 18 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 19 recites “The method of claim 1, wherein the actual measurement data comprises data measured before starting the process and data measured after starting the process, and wherein the method further comprises:
updating the actual process data and the actual measurement data;
updating the process model and the measurement model based on updated actual process data and updated actual measurement data;
applying the simulation process data to the actual manufacturing process of the display panel in response to verifying that the simulation process data is applicable to actual production; and
forming the simulation process data which is verified to be applicable to actual production into a manufacturing process file.”
This limitation merely further specifies updating the actual process data and actual measurement data, updating the process model and measurement model based on the updated data, applying the simulation process data to the actual manufacturing process in response to a positive verification result, and forming the verified simulation process data into a manufacturing process file. The updating and applying limitations merely instruct implementation of the recited data/model processing activity at a high level of generality, without specifying a particular technological manner of performing the operations. See MPEP § 2106.05(f). The forming limitation merely converts the verified simulation process data into a manufacturing process files and merely an recitation of insignificant post-solution activity, such as data outputting. See MPEP § 2106.05(g). Thus, the limitations do not integrate the judicial exception into a practical application and amount to significantly more than the judicial exception. Therefore, the claim 19 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 27 recites “The method of claim 26, wherein performing at least one process of the display panel in the physical manufacturing process comprises:
sequentially performing a pre-measurement operation, a preparation operation, a loading process data operation, a processing operation, and a post-measurement operation,
wherein the actual process data is loaded in the loading process data operation, and the actual measurement data is generated in at least one of the pre-measurement operation, the processing operation and the post-measurement operation.”
This limitation merely further specifies the physical manufacturing process of claim 26 by requiring sequential performance of operation, and by specifying that actual process data is loaded during the loading operation and actual measurement data is generated during at least one of the pre-measurement, processing, and post measurement operations. The loading of actual process data and generation of actual measurement data merely an recitation of insignificant extra-solution activity such as data gathering. See MPEP § 2106.05(g). Further, the preparation and processing operations are recited at a high level of generality, without specifying any particular manner of performing the operations or any unconventional use of a manufacturing machinery. Thus, these limitations merely invoke machinery in its ordinary capacity to perform the recited physical process and do not integrate the judicial exception into a practical application and amount to significantly more than the judicial exception. See MPEP § 2106.05(f). Therefore, the claim 27 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 28 recites “The method of claim 26, further comprising:
applying the simulation process data as actual process data to the loading process data operation in the physical manufacturing process, in response to verifying that the simulation process data is applicable to actual production.”
This limitation merely further specifies that, after the simulation process data is verified as applicable to actual production, the verified simulation process data is applied as actual process data to the loading process data operation of the physical manufacturing process. The limitation merely recites insignificant post solution activity because it applies the result of the recited analysis at a high level without requiring any particular manner of controlling or performing the physical manufacturing process using the verified data. Thus, the limitation does not integrate the judicial exception into a practical application and amount to significantly more than the judicial exception. See MPEP § 2106.05(g). Therefore, the claim 28 does not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim 29 recites “The method of claim 26,further comprising:
re-performing the physical manufacturing process to generate new actual process data and new actual measurement data; and
updating the process model and the measurement model based on the new actual process data and the new actual measurement data.”
This limitation merely further specifies the physical manufacturing and model processing operations by re-performing the physical manufacturing process to generate new actual process data and new actual measurement data, and updating the process model and the measurement model based on the new data. The re-performing limitation merely invokes the physical manufacturing process at a high level without requiring any particular modification or unconventional operation of the manufacturing process or machinery. The updating limitation merely applies the newly generated data to update the models without specifying any particular technological manner or mechanism for performing the update. Thus, the limitations do not integrate the judicial exception into a practical application and amount to significantly more than the judicial exception. See MPEP § 2106.05(f). Therefore, the claim 29 does not recite patent eligible subject matter under 35 U.S.C. § 101.
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.
Claim(s) 1-2,13, 15, 17-19, 23-24 and 26-29 are rejected under 35 U.S.C. 103 as being unpatentable
over Yoshii US20090233194A1 in view of Cheng US20070282767A1.
Claim 1, Yoshii teaches A method of verifying process data of a display panel ([0061] … Process parameters for forming a process image meeting an evaluation criterion are determined from the process image calculated by the process simulator 300. [0062] … Consequently, the exposure system 1 can economically provide a high-quality device (e.g., a semiconductor element, LCD element, imaging element (CCD or the like), or thin-film magnetic head) with high throughput.), comprising:
generating, based on design data of a process of the display panel, simulation process data for performing the process ([0027] The reticle 113 has a reticle pattern, and is positioned by the reticle stage 114. The reticle pattern is a pattern to be transferred onto the wafer 116, and includes circuit patterns of a plurality of elements forming a device such as a semiconductor device, liquid crystal display device, or thin-film magnetic head. [0045] First, in step S1002, the controller 120 sets optical parameters including the information of the reticle 113 and the information of the exposure conditions … The information of the reticle 113 contains information such as the two-dimensional shapes, transmittances, and phases of the reticle pattern and background. [0046] Then, in step S1004, the optical simulator 200 (CPU 210) calculates a light intensity distribution to be formed on the wafer 116, based on the optical parameters … In other words, the optical simulator 200 calculates a light intensity distribution corresponding to the reticle pattern based on the optical parameters set in step S1002. [0051] As described above, the optical parameters for forming the resist image meeting the evaluation criterion can be obtained within a short time period by repetitively calculating the light intensity distribution and resist image while changing the optical parameters by using the optical simulator 200 (first prediction). Examiner note: the reticle pattern information corresponds to design data of the lithography process. The first prediction uses the reticle pattern information to obtain optical parameters, which correspond to the simulation process data for performing the process);
performing, by using a process model, a simulation of performing the process based on the simulation process data ([0052] Subsequently, in step S1014, the process simulator 300 (CPU 310) calculates a light intensity distribution to be formed on the wafer 116, based on the optical parameters input from the optical simulator 200 across the network. [0054] Then, in step S1018, the process simulator 300 (CPU 310) calculates (predicts) a process image based on the light intensity distribution calculated in step S1014 and the process parameters set in step S1016. When calculating (predicting) a process image, the process simulator 300 uses a pregenerated process model. [0055] The process simulator 300 uses the process model and hence can calculate a process image corresponding to both the optical parameters and process parameters. Examiner note: the pregenerated process model corresponds to the process model. The process simulator calculates a light intensity distribution based on the optical parameters (i.e., simulation process data) and then calculates a corresponding process image using the pregenerated process model, which corresponds to performing a simulation of performing the process based on the simulation process data); and
verifying, ([0056] In step S1020, the process simulator 300 (CPU 310) evaluates (second evaluation) whether the process image calculated in step S1018 is a process image meeting an evaluation criterion (second evaluation criterion). The process image meeting the evaluation criterion includes not only a process image having a target shape (to be formed), but also a process image having a shape falling within an allowable range of the target shape. [0060] On the other hand, if the process image calculated in step S1018 is the process image meeting the evaluation criterion, optical parameters and process parameters for implementing desired performance are determined in step S1028. [0062] The optical parameters determined by the parameter determination method of this embodiment are set in the exposure apparatus 100, and the wafer 116 coated with a resist represented by the process parameters determined by the parameter determination method of this embodiment is exposed. Examiner note: The optical parameters as simulation process data, are used to calculate the simulated process image, and evaluating the simulated process image against an evaluation criterion, and when the image satisfies the criterion, the corresponding parameters are determined and subsequently used in the actual exposure process),
wherein the process model is constructed based on actual process data generated in an actual manufacturing process of the display panel, ([0080] In step S3004, process parameters including the information of a resist to be used when generating a process model and the information of processes are set. [0081] In step S3006, the exposure conditions and test reticle set in step S3002 are set in the exposure apparatus 100, and the wafer 116 coated with the resist set in step S3004 is exposed. [0082] In step S3008, the processes set in step S3004 are performed on the wafer 116 exposed in step S3006 … [0085] In step S3014, a process image corresponding to the light intensity distribution calculated in step S3012 is calculated, based on the process parameters set in step S3004. [0086] In step S3016, a process model is generated from the dimension (shape) of the test pattern formed on the wafer 116 and the film thickness of the resist in the region having no light-shielding portion, both of which are measured in step S3010, and the process image calculated in step S3014. [0089] A method of fabricating a device (e.g., a semiconductor IC element or liquid crystal display element) using the above-mentioned exposure apparatus will be explained below. The device is fabricated through a step of setting the exposure conditions determined as described previously in the exposure apparatus, and exposing a substrate (e.g., a wafer or glass substrate) coated with a photosensitive agent … a step of developing the substrate … Examiner note: the process parameters set in step S3004 and used in the actual exposure and physical processing sequence correspond to the actual process data generated in the actual manufacturing process, and calculating the process image based on those process parameters and subsequently uses that process image in generating the process model. Thus, the process model is constructed based on the actual process data).
However, Yoshii fails to teach using a measurement model for the verification, wherein the measurement model is constructed based on actual process data and actual measurement data which are generated in the actual manufacturing process of the display panel.
Cheng teaches using a measurement model for the verification, wherein the measurement model is constructed based on actual process data and actual measurement data which are generated in the actual manufacturing process of the display panel ([0003] … the present invention relates to a method for evaluating reliance level of the virtual metrology system suitable for use in production equipment of a semiconductor or thin film transistor liquid crystal display (TFT-LCD) plant. [0014] In the training phase, at first, a plurality of sets of historical process data belonging to a piece of production equipment are obtained, wherein each set of the historical process data includes process parameters and the data corresponding thereto. Meanwhile, a plurality of sets of historical process data belonging to a piece of production equipment are obtained … a plurality of historical actual measurement values are also obtained from a piece of measurement equipment, wherein the historical actual measurement values are the measurement values of the products which are manufactured in accordance with the sets of historical process data respectively … a reference model is established by using the same sets of historical process data and the same historical actual measurement values … [0041] The explanation herein adopts a neural-network (NN) algorithm as the conjecture algorithm for establishing the conjecture model performing virtual measurement, and uses such as a multi-regression (MR) algorithm to be the reference algorithm for establishing the reference model that serves as a comparison base for the conjecture model. [0043] The RI is designed to gauge the reliance level of the virtual measurement value … However, when virtual metrology is applied, no actual measurement value can be used to verify the trustworthiness of the virtual measurement value … Instead, the present invention adopts the statistical distribution Zŷ ri estimated by the reference algorithm … to replace Zy i . [0046] The RI increases with increasing overlap area A. This phenomenon indicates that the result obtained using the conjecture model is closer to that obtained from the reference model, and thus the corresponding virtual measurement value is more reliable. Examiner note: the reference teaches reference model corresponds to the measurement model because it is constructed using historical process data from production equipment and corresponding actual measurement values of products manufactured according to the process data. The reference further teaches using the reference model as a comparison basis to evaluate the reliability of a virtual measurement result when an actual measurement values is unavailable. The reference also teaches the virtual metrology system is applicable to production equipment of a TFT-LED plant)
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yoshii to incorporate the teaching of Cheng, and apply a reference model constructed using historical process data and corresponding historical actual measurement values as a comparison basis for evaluating a virtual measurement result, in order to provide an independent reliable assessment of Yoshii’s simulated process results when a current actual measurement is unavailable, thereby increasing confidence in selecting process parameters for manufacturing whole reducing the need for additional physical measurements and associated metrology time.
Claim 2, Yoshii teaches The method of claim 1, wherein the performing, by using a process model, a simulation of performing the process based on the simulation process data comprises: determining, by using the process model, feature data of the display panel achievable by performing the process based on the simulation process data ([0054] Then, in step S1018, the process simulator 300 (CPU 310) calculates (predicts) a process image based on the light intensity distribution calculated in step S1014 and the process parameters set in step S1016. When calculating (predicting) a process image, the process simulator 300 uses a pregenerated process model. [0055] The process simulator 300 uses the process model and hence can calculate a process image corresponding to both the optical parameters and process parameters. [0008] … the process simulator calculates a step of developing a resist exposed by an optical image while changing process (non-optical) parameters … thereby predicting a shape (process image) to be formed after an etching process. Examiner note: the predicted process image corresponds to the feature data because the process image represents the predicted shape obtainable after performing the fabrication process. The reference further teaches determining the process image using the pregenerated process model based on the optical and process parameters supplied to the process simulator).
Claim 13, Yoshii teaches The method of claim 1, wherein the process of the display panel comprises a backplane manufacturing process that includes a lithography process for forming a film layer, the design data comprises a design pattern of a mask ([0026] The exposure unit 110 transfers the pattern of a reticle or mask onto a substrate such as a wafer by using the step-and-scan method, the step-and-repeat method, or another exposure method. [0027] The reticle 113 has a reticle pattern, and is positioned by the reticle stage 114. The reticle pattern is a pattern to be transferred onto the wafer 116, and includes circuit patterns of a plurality of elements forming a device such as a semiconductor device, liquid crystal display device, or thin-film magnetic head. [0030] … Since the resist applied on the wafer 116 is exposed to this light intensity distribution, a latent image pattern is formed. This latent image pattern is formed into a process image (resist pattern) through processes such as processes of developing and etching the wafer 116 (resist). [0089] A method of fabricating a device (e.g., a semiconductor IC element or liquid crystal display element) using the above-mentioned exposure apparatus will be explained below. The device is fabricated through a step of setting the exposure conditions determined as described previously in the exposure apparatus, and exposing a substrate (e.g., a wafer or glass substrate) coated with a photosensitive agent … a step of developing the substrate … Examiner note: the reference teaches applying mask pattern lithography process to fabrication of a liquid crystal display element on a glass substrate. The disclosed LED circuit pattern exposure, development, and etching process corresponds to the backplane manufacturing process including a lithography process, and the reticle or mask pattern corresponds to the design pattern of the mask), and the generating, based on design data of a process of the display panel, simulation process data for performing the process comprises at least one of:
simulating at least a part of the design pattern of the mask to obtain a test pattern;
generating an exposure process parameter based on a received exposure parameter setting information;
generating a resist process parameter based on a received resist parameter setting information ([0053] In step S1016, the controller 120 sets process parameters including the information of a resist to be applied on the wafer 116 and the information of processes to be performed by the processing apparatus, based on user's instructions input via the input unit 126. The resist information contains information such as the absorption coefficient of light, the diffusion length of an acid, the residual film thickness-to-dose relationship, the influence of a basic contaminant, the film thickness, the presence/absence of an antireflection film, and the reflectance. Examiner note: the user instructions input via the input unit correspond to the received resist parameter setting information, and the resist related process parameters set by the controller correspond to the generated resist process parameter); or
generating a development process parameter based on a received development parameter setting information.
Claim 15, Yoshii teaches The method of claim 13, wherein:
the exposure process parameter comprises at least one of a numerical aperture, a wavelength, a coherence factor, an illumination type, an exposure magnification, and a focus position ([0045] First, in step S1002, the controller 120 sets optical parameters including the information of the reticle 113 and the information of the exposure conditions, based on user's instructions input via the input unit 126. The information of the reticle 113 contains information such as the two-dimensional shapes, transmittances, and phases of the reticle pattern and background. The information of the exposure conditions contains any of information pertaining to the light source and exposure apparatus, e.g., the wavelength of light emitted from the light source 111, the secondary light source distribution (shape) formed by the illumination optical system 112, the polarized light distribution, the cumulative exposure amount, and the numerical aperture, wavefront aberration, pupil transmittance distribution, and polarization characteristics of the projection optical system 115. The exposure condition information may also contain information such as … a defocusing amount …); and
the resist process parameter comprises at least one of a type of photoresist, a thickness and development rate of photoresist, a substrate material, or a concentration distribution of photosensitive compound (PAC) ([0053] In step S1016, the controller 120 sets process parameters including the information of a resist to be applied on the wafer 116 and the information of processes to be performed by the processing apparatus, based on user's instructions input via the input unit 126. The resist information contains information such as the absorption coefficient of light, the diffusion length of an acid, the residual film thickness-to-dose relationship, the influence of a basic contaminant, the film thickness, the presence/absence of an antireflection film, and the reflectance. The process information contains information such as the time and temperature of soft-baking performed after resist coating, the standing time after exposure, the PEB temperature, the PEB time, the developer, the developing rate, and the etching rate.).
Claim 17, Yoshii teaches The method of claim 13, wherein the generating, based on design data of a process of the display panel, simulation process data for performing the process further comprises at least one of:
performing lens projection simulation on the test pattern based on the exposure process parameter to obtain aerial image data ([0065] … In step S2002, optical parameters including the information of a test reticle and the information of exposure conditions are set. Unlike the reticle 113, the test reticle has a test pattern for generating a light intensity distribution model … The exposure condition information indicates exposure conditions to be set in the exposure apparatus 100 when generating a light intensity distribution model. [0070] In step S2012, the optical parameters (test reticle information and exposure condition information) set in step S2002 are input to the optical simulator 200, and a light intensity distribution is calculated. [0007] The optical simulator calculates a light intensity distribution (optical image) to be formed on the image plane of a projecting optical system while changing optical parameters (e.g., information pertaining to the reticle pattern and exposure conditions), thereby predicting a shape (resist image) to be formed on a resist. Examiner note: the test pattern of the test reticle corresponds to the claimed test pattern, and the exposure condition information corresponds to the exposure process parameter. The reference teaches inputting the test reticle and exposure condition information to the optical simulator to calculate a light intensity distribution or optical image on the image plane of a projecting optical system, which corresponds to performing lens projection simulation to obtain aerial image data); or
generating graphic data of the film layer which has been developed, based on the development parameter.
Claim 18, Yoshii teaches The method of claim 17, further comprising:
presenting at least one of the aerial image data and the graphic data through a user interaction interface and receiving an input from a user ([0007] The optical simulator calculates a light intensity distribution (optical image) to be formed on the image plane of a projecting optical system while changing optical parameters (e.g., information pertaining to the reticle pattern and exposure conditions), thereby predicting a shape (resist image) to be formed on a resist. [0033] The input unit 230 includes, for example, a keyboard, communication interface, and media reader. The output unit 240 includes, for example, a display and communication interface. [0045] First, in step S1002, the controller 120 sets optical parameters including the information of the reticle 113 and the information of the exposure conditions, based on user's instructions input via the input unit 126. Examiner note: the light intensity distribution or optical image corresponds to the claimed aerial image data. The reference further teaches that the optical simulator generating the optical image including a display output and an input interface, and that user instructions are received for setting the exposure related optical parameters), and
adjusting at least one of the exposure process parameter, the resist process parameter and the development process parameter based on the input from the user ([0042] In the exposure system 1 of this embodiment, a resist image or process image is predicted while changing optical parameters settable in the exposure apparatus 100, and optical parameters for forming a process image having a predetermined shape are determined and set in the exposure apparatus 100. [0045] First, in step S1002, the controller 120 sets optical parameters including the information of the reticle 113 and the information of the exposure conditions, based on user's instructions input via the input unit 126. The information of the reticle 113 contains information such as the two-dimensional shapes, transmittances, and phases of the reticle pattern and background. The information of the exposure conditions contains any of information pertaining to the light source and exposure apparatus, e.g., the wavelength of light emitted from the light source 111, the secondary light source distribution (shape) formed by the illumination optical system 112, the polarized light distribution, the cumulative exposure amount, and the numerical aperture, wavefront aberration, pupil transmittance distribution, and polarization characteristics of the projection optical system 115. [0049] If the resist image calculated in step S1006 is not the resist image meeting the evaluation criterion, the optical simulator 200 instructs the exposure apparatus 100 to change the optical parameters. In step S1010, the controller 120 changes the optical parameters. The process then returns to step S1002, the controller 120 sets the optical parameters changed in step S1010, and the optical simulator 200 (CPU 210) executes steps S1004, S1006, and S1008 by using the changed optical parameters. Examiner note: the exposure condition information corresponds to the exposure process parameter. The reference teaches predicting the resist/process image while changing the optical parameters and sets those exposure related parameters based on user instruction received through the input unit).
Claim 19, Yoshii teaches The method of claim 1, wherein the actual measurement data comprises data measured before starting the process and data measured after starting the process ([0029] The measurement unit 118 measures an illumination shape (effective light source distribution) formed by the illuminating optical system 112, the pupil plane aberration distribution of the projecting optical system 115, and the polarized light distributions of the illumination optical system 112 and projection optical system 115. [0081] In step S3006, the exposure conditions and test reticle set in step S3002 are set in the exposure apparatus 100, and the wafer 116 coated with the resist set in step S3004 is exposed. [0082] In step S3008, the processes set in step S3004 are performed on the wafer 116 exposed in step S3006. [0083] In step S3010, the CD measurement apparatus 400 measures the dimension (shape) of the test pattern formed on the wafer 116, and the film thickness measurement apparatus 500 measures the film thickness of the resist in the region having no light-shielding portion. Examiner note: the measurement of the exposure apparatus optical conditions correspond to measurement data obtained before performing the fabrication process. After the wafer is exposed and processed, measuring the resulting test pattern dimension and resist thickness, corresponding to measurement data obtained after starting the process), and wherein the method further comprises:
updating the actual process data and the actual measurement data ([0078] The process model generation method will now be explained with reference to FIG. 9. The settings of the initial values of process parameters are explained in detail by well-known process simulators (e.g., Prolith of KLA-tencor, SOLID-E of Synopsys, and EM-suite of Panoramic Technology), so a detailed explanation will be omitted. The following explanation exemplifies a method of tuning (adjusting) process parameters in accordance with the exposure results, after the initial values of the process parameters are set. [0082] Also, a residual film of the resist is formed in the region having no light-shielding portion, while sequentially changing the exposure amount. [0083] In step S3010, the CD measurement apparatus 400 measures the dimension (shape) of the test pattern formed on the wafer 116, and the film thickness measurement apparatus 500 measures the film thickness of the resist … Examiner note: the reference teaches adjusting the process parameters from initial values have been set and sequentially changing the exposure amount, which correspond to updating the actual process data. The reference further teaches measuring the resulting test pattern dimension and resist film thickness under the changed process conditions, which corresponds to updating the actual measurement data);
updating the process model ([0086] In step S3016, a process model is generated from the dimension (shape) of the test pattern formed on the wafer 116 and the film thickness of the resist in the region having no light-shielding portion, both of which are measured in step S3010, and the process image calculated in step S3014. [0008] In the process simulator, process models corresponding to actual processes … are prepared, and various parameters of these process models are fed back from the exposure results. Examiner note: the reference teaches feeding exposure results back to the parameters of the process model. The reference further teaches generates the process model using the resulting test pattern dimension and resist film thickness measurements together with the corresponding calculated process image, which correspond to updating the process model based on updated actual process data and updated actual measurement data);
applying the simulation process data to the actual manufacturing process of the display panel in response to verifying that the simulation process data is applicable to actual production ([0056] In step S1020, the process simulator 300 (CPU 310) evaluates (second evaluation) whether the process image calculated in step S1018 is a process image meeting an evaluation criterion … [0060] On the other hand, if the process image calculated in step S1018 is the process image meeting the evaluation criterion, optical parameters and process parameters for implementing desired performance are determined in step S1028. [0062] The optical parameters determined by the parameter determination method of this embodiment are set in the exposure apparatus 100, and the wafer 116 coated with a resist represented by the process parameters determined by the parameter determination method of this embodiment is exposed. A process image having a predetermined shape can be formed by performing, on the exposed wafer 116, processes represented by the process parameters determined by the parameter determination method of this embodiment.); and
forming the simulation process data which is verified to be applicable to actual production into a manufacturing process file ([0031] … The exposure conditions (exposure recipe) for exposing the wafer 116 are input via the input unit 126, stored in the memory 124, and set in the exposure apparatus 100 by the CPU 122. [0032] … outputs the determined optical parameters to the exposure apparatus 100 so that the resist image meets an evaluation criterion. [0060] … if the process image calculated in step S1018 is the process image meeting the evaluation criterion, optical parameters and process parameters for implementing desired performance are determined in step S1028. See also [0089]).
However, Yoshii fails to teach updating the measurement model based on updated actual process data and updated actual measurement data.
Cheng teaches updating the measurement model based on updated actual process data and updated actual measurement data ([0017] Thereafter, in the tuning phase, at first, a set of tuning-use process data are obtained from the aforementioned production equipment, and a tuning-use actual measurement value is obtained from the aforementioned measurement equipment, wherein the tuning-use actual measurement value is the measurement value of the product which is manufactured in accordance with the set of tuning-use process data. Then, the conjecture model is adjusted by using the tuning-use process data and the tuning-use actual measurement value. And, the reference model is adjusted by using the tuning-use process data and the tuning-use actual measurement value. [0087] Production equipment is a time-varying system, and Its property will drift or shift over time. Execution of maintenance or part-replacement may also alter the properties of the production equipment. To remedy the problem of property-drift, the conjecture and reference models should be tuned by a fresh actual measurement sample. In general, the set of tuning-use process data is adopted after the sets of historical process data … [0089] The standardized historical data sets including Zx a,j , (a=1,2, . . . ,n; j=1,2, . . . ,p) and Zy a , (a=1,2, . . .,n) as well as the tuning-use data set including (Zx n+1,j ,j=1,2, . . . ,p) and (Zy n+1 ) are utilized to tune the MR reference model (step 250). Examiner note: the MR reference model corresponds to the measurement model. The newly obtained tuning-use process data and corresponding actual measurement value corresponds to updated actual process data and updated actual measurement data, and using those new data to tune, i.e., update, the MR reference model).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yoshii to incorporate the teaching of Cheng, and apply tuning of the reference model using newly obtained process data and corresponding actual measurement data, in order to compensate for drift or shifts in production equipment over time, thereby maintaining the accuracy and reliability of the reference model for evaluating subsequent production process data.
Claim 26, Yoshii teaches A method of manufacturing a display panel, comprising a physical manufacturing process and a digital processing process (Fig.1;[0024] the exposure system 1 includes an exposure apparatus 100, optical simulator 200, process simulator 300, critical dimension measurement apparatus (to be referred to as a CD measurement apparatus hereinafter) 400, and film thickness measurement apparatus 500. See also [0042] and [0089]), wherein:
in the physical manufacturing process, at least one process of the display panel is performed, so as to obtain actual process data and actual measurement data ([0080] In step S3004, process parameters including the information of a resist to be used when generating a process model and the information of processes are set. [0081] In step S3006, the exposure conditions and test reticle set in step S3002 are set in the exposure apparatus 100, and the wafer 116 coated with the resist set in step S3004 is exposed. [0082] In step S3008, the processes set in step S3004 are performed on the wafer 116 exposed in step S3006. [0083] In step S3010, the CD measurement apparatus 400 measures the dimension (shape) of the test pattern formed on the wafer 116, and the film thickness measurement apparatus 500 measures the film thickness of the resist …); and
in the digital processing process, the method of claim 1 is performed by using a process model and a measurement model which are generated based on the actual process data and the actual measurement data, so as to verify whether simulation process data is applicable to actual production (See Claim 1 discussed above).
Claim 27, Yoshii teaches The method of claim 26, wherein performing at least one process of the display panel in the physical manufacturing process comprises:
sequentially performing a pre-measurement operation, a preparation operation, a loading process data operation, a processing operation, and a post-measurement operation ([0028] The wafer 116 is coated with a resist as a photosensitive agent, and positioned by the wafer stage 117. The wafer 116 is sometimes replaced with a glass plate or another substrate. – Note: preparation operation. [0029] The measurement unit 118 measures an illumination shape (effective light source distribution) formed by the illuminating optical system 112, the pupil plane aberration distribution of the projecting optical system 115, and the polarized light distributions of the illumination optical system 112 and projection optical system 115. – Note: pre-measurement operation. [0031] In the exposure apparatus 100 shown in FIG. 1, the controller 120 includes a CPU 122, memory 124, input unit 126, and output unit 128, and controls the whole (operation) of the exposure apparatus 100. The exposure conditions (exposure recipe) for exposing the wafer 116 are input via the input unit 126, stored in the memory 124, and set in the exposure apparatus 100 by the CPU 122. [0081] In step S3006, the exposure conditions and test reticle set in step S3002 are set in the exposure apparatus 100, and the wafer 116 coated with the resist set in step S3004 is exposed. – Note: loading process data operation. [0082] In step S3008, the processes set in step S3004 are performed on the wafer 116 exposed in step S3006. In this way, the test pattern is formed on the wafer 116. – Note: processing operation. [0083] In step S3010, the CD measurement apparatus 400 measures the dimension (shape) of the test pattern formed on the wafer 116, and the film thickness measurement apparatus 500 measures the film thickness of the resist in the region having no light-shielding portion. – Note: post-measurement operation. Examine note: the measurement of the exposure apparatus optical conditions corresponds to the pre-measurement operation because it provides process device measurement data before processing. Coating and positioning the water corresponds to the preparation operation. The exposure recipe input and set in the exposure apparatus corresponds to the loading process data operation. The reference further teaches performing the physical process on the wafer and subsequently measures the resulting test pattern dimension and resist film thickness, corresponding respectively to the processing and post-measurement operations),
wherein the actual process data is loaded in the loading process data operation, and the actual measurement data is generated in at least one of the pre-measurement operation, the processing operation and the post-measurement operation ([0031] In the exposure apparatus 100 shown in FIG. 1, the controller 120 includes a CPU 122, memory 124, input unit 126, and output unit 128, and controls the whole (operation) of the exposure apparatus 100. The exposure conditions (exposure recipe) for exposing the wafer 116 are input via the input unit 126, stored in the memory 124, and set in the exposure apparatus 100 by the CPU 122. [0083] In step S3010, the CD measurement apparatus 400 measures the dimension (shape) of the test pattern formed on the wafer 116, and the film thickness measurement apparatus 500 measures the film thickness of the resist in the region having no light-shielding portion.).
Claim 28, Yoshii teaches The method of claim 26, further comprising:
applying the simulation process data as actual process data to the loading process data operation in the physical manufacturing process, in response to verifying that the simulation process data is applicable to actual production ([0056] In step S1020, the process simulator 300 (CPU 310) evaluates (second evaluation) whether the process image calculated in step S1018 is a process image meeting an evaluation criterion (second evaluation criterion). The process image meeting the evaluation criterion includes not only a process image having a target shape (to be formed), but also a process image having a shape falling within an allowable range of the target shape. [0060] On the other hand, if the process image calculated in step S1018 is the process image meeting the evaluation criterion, optical parameters and process parameters for implementing desired performance are determined in step S1028. More specifically, the optical parameters set in step S1002 and the process parameters set in step S1016 are determined as the optical parameters and process parameters for implementing desired performance. [0062] The optical parameters determined by the parameter determination method of this embodiment are set in the exposure apparatus 100, and the wafer 116 coated with a resist represented by the process parameters determined by the parameter determination method of this embodiment is exposed. A process image having a predetermined shape can be formed by performing, on the exposed wafer 116, processes represented by the process parameters determined by the parameter determination method of this embodiment.).
Claim 29, Yoshii teaches The method of claim 26,further comprising:
re-performing the physical manufacturing process to generate new actual process data and new actual measurement data ([0078] The following explanation exemplifies a method of tuning (adjusting) process parameters in accordance with the exposure results, after the initial values of the process parameters are set. [0081] In step S3006, the exposure conditions and test reticle set in step S3002 are set in the exposure apparatus 100, and the wafer 116 coated with the resist set in step S3004 is exposed. [0082] In step S3008, the processes set in step S3004 are performed on the wafer 116 exposed in step S3006. In this way, the test pattern is formed on the wafer 116. Also, a residual film of the resist is formed in the region having no light-shielding portion, while sequentially changing the exposure amount. [0083] In step S3010, the CD measurement apparatus 400 measures the dimension (shape) of the test pattern formed on the wafer 116, and the film thickness measurement apparatus 500 measures the film thickness of the resist in the region having no light-shielding portion. Examiner note: the reference teaches performing the physical exposure and processing after initial process parameter values have been set and sequentially changes the exposure amount during the physical process. The changed exposure conditions correspond to new actual process data, and the resulting test pattern dimension and resist film thickness measurement correspond to new actual measurement data); and
updating the process model and ([0086] In step S3016, a process model is generated from the dimension (shape) of the test pattern formed on the wafer 116 and the film thickness of the resist in the region having no light-shielding portion, both of which are measured in step S3010, and the process image calculated in step S3014. [0008] In the process simulator, process models corresponding to actual processes … are prepared, and various parameters of these process models are fed back from the exposure results. Examiner note: the reference teaches feeding exposure results back to the parameters of the process model. The reference further teaches generates the process model using the resulting test pattern dimension and resist film thickness measurements together with the corresponding calculated process image, which correspond to updating the process model based on updated actual process data and updated actual measurement data).
However, Yoshii fails to teach updating the measurement model based on the new actual process data and the new actual measurement data.
Cheng teaches updating the measurement model based on the new actual process data and the new actual measurement data ([0017] Thereafter, in the tuning phase, at first, a set of tuning-use process data are obtained from the aforementioned production equipment, and a tuning-use actual measurement value is obtained from the aforementioned measurement equipment, wherein the tuning-use actual measurement value is the measurement value of the product which is manufactured in accordance with the set of tuning-use process data. Then, the conjecture model is adjusted by using the tuning-use process data and the tuning-use actual measurement value. And, the reference model is adjusted by using the tuning-use process data and the tuning-use actual measurement value. [0087] Production equipment is a time-varying system, and Its property will drift or shift over time. Execution of maintenance or part-replacement may also alter the properties of the production equipment. To remedy the problem of property-drift, the conjecture and reference models should be tuned by a fresh actual measurement sample. In general, the set of tuning-use process data is adopted after the sets of historical process data … [0089] The standardized historical data sets including Zx a,j , (a=1,2, . . . ,n; j=1,2, . . . ,p) and Zy a , (a=1,2, . . .,n) as well as the tuning-use data set including (Zx n+1,j ,j=1,2, . . . ,p) and (Zy n+1 ) are utilized to tune the MR reference model (step 250). Examiner note: the MR reference model corresponds to the measurement model. The newly obtained tuning-use process data and corresponding actual measurement value corresponds to the new actual process data and new actual measurement data, and using those new data to tune, i.e., update, the MR reference model).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yoshii to incorporate the teaching of Cheng, and apply tuning of the reference model using newly obtained process data and corresponding actual measurement data, in order to compensate for drift or shifts in production equipment over time, thereby maintaining the accuracy and reliability of the reference model for evaluating subsequent production process data.
The elements of claims 23-24 substantially the same as those of claim 1. Therefore, the elements of claims 23-24 are rejected due to the same reasons as outlined above for claim 1. Further. The additional limitation of claims 23-24, “An electronic device, comprising a memory and a processor, wherein the memory stores instructions executable by the processor, and the instructions, when executed by the processor, cause the processor to implement …” and “A non-transitory computer readable storage medium storing computer instructions, wherein the computer instructions are configured to cause a computer to implement …” (See Yoshii, FIG.1 and [0031]).
Claim(s) 3 is rejected under 35 U.S.C. 103 as being unpatentable over Yoshii in view of Cheng as
applied to claim 1 above, and further in view of Jebri (“Virtual Metrology applied in Run-to-Run Control for a Chemical Mechanical Planarization process,” published in 2017) and Guo CN109491216B.
Claim 3, Yoshii in view of Cheng teaches the method of claim 1 as discussed above. Yoshii teaches the simulation process data and the feature data output by the process model and determining that the simulation process data is applicable to actual production (See Yoshii, [0054]-[0056], [0060] and [0062]), further teaches feature data of the display panel obtained by actually performing the process ([0067]-[0069]). Cheng teaches the measurement model constructed based on actual process data and actual measurement data (See Cheng, [0014] and [0018]).
However, Yoshii in view of Cheng fails to teach, but Jebri teaches determining, among the actual process data, actual process data having a similarity higher than a preset similarity threshold with respect to the process data, as similar process data by using model (Page.5, III-A. JITL approach description, “the ETM variables (collected data from equipment), denoted by xj(k), are measured or collected during the entire processing task (or run) … In this step, all anterior ETM variables of the complete database are extracted when the DTMs were measured, which gives a collection [Xc;Yc] of Nc data. Then, the current ETM xj(k) is compared to all xc variables. Such a comparison is achieved by using the similarity criterion (6) … Then, a threshold of similarity Smin is defined. This means that the observations xj(k) and xc(i) are considered as similar if the following inequality holds: Si(xj(k),xc(i)) ≥ Smin (7) Then, M data of the database which satisfy the last condition (Eq.7) are selected and noted [XM;YM].” Examiner note: the reference teaches comparing current process data xj(k) with historical process data xc(i), determining similarity using an expressly defined similarity criterion and preset similarity threshold Smin, and selecting the historical data satisfying the threshold as similar data XM);
determining, among the actual measurement data, feature data based on the similar process data, as actual feature data (Page.2, “…using the old sampled measurement yj(k) with their corresponding old process information xj(k).” Page.5, III-A. JITL approach description, “the ETM variables (collected data from equipment), denoted by xj(k), are measured or collected during the entire processing task (or run). They have also a direct impact on wafer properties which are defined throughout DTM variables denoted by yj(k).… In this step, all anterior ETM variables of the complete database are extracted when the DTMs were measured, which gives a collection [Xc;Yc] of Nc data … Then, M data of the database which satisfy the last condition (Eq.7) are selected and noted [XM;YM].” Examiner note: the reference teaches historical actual measurement data Yc corresponding to historical process data Xc. After historical process data satisfying the similarity criterion are selected as XM, their corresponding measured DTM values are selected as YM, wherein the DTM values represent measured wafer properties).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yoshii in view of Cheng to further incorporate the teaching of Jebri, and apply a similarity criterion and preset similarity threshold to select historical process data sufficiently similar to a current query process record together with the corresponding historical actual measurement data, in order to identify historical manufacturing data representative of Yoshii’s candidate simulation process data, thereby improving the reliability of determining whether the candidate process parameters are suitable for actual production.
However, Yoshii in view of Cheng and Jebri fails to teach, but Guo teaches in response to a difference between the actual data and the data output being less than a preset difference threshold (Page.2., “S02: Combine the above-mentioned simulated best focal length with the measured online process data to predict the lithography results of the entire wafer to obtain the predicted results, and measure the actual results after the wafer lithography; S03: Perform automatic verification on the predicted result and the actual result. If the error between the predicted result and the actual result is less than the threshold, keep the predicted result and go to step S04; if the error between the predicted result and the actual result is greater than or equal to the threshold, Then return to step S01; S04: Optimize the parameters of the actual photolithography process by using the predicted results retained above.” Examiner note: the reference teaches automatically comparing a predicted lithography result with an actual lithography result and accepting the predicted result when the error between the predicted and actual results is less than a threshold, which correspond to determination based on a preset difference threshold).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yoshii in view of Cheng and Jebri to further incorporate the teaching of Guo, and apply automatic comparing a predicted lithography result and accepting the predicted result when the error is below a threshold, in order to confirm that the simulated result sufficiently corresponds to the actual manufacturing result before relying on the simulated process parameters, thereby improving the reliability of determining whether the process parameters are suitable for actual production.
Claim(s) 4 is rejected under 35 U.S.C. 103 as being unpatentable over Yoshii in view of Cheng as
applied to claim 1 above, and further in view of Tsai US20100312374A1.
Claim 4, Yoshii in view of Cheng teaches the method of claim 1 as discussed above. Yoshii teaches the actual process data, simulation process data and the feature data output by the process model and determining that the simulation process data is applicable to actual production (See Yoshii, [0054]-[0056], [0060] and [0062]). Cheng teaches the measurement model constructed based on actual process data and actual measurement data (See Cheng, [0014] and [0018]).
However, Yoshii in view of Cheng fails to teach, but Tsai teaches calculating a process fluctuation by applying a feedback parameter algorithm to the data by using a control model ([0020] … the VM model 166 includes a Y2Y adjustment unit 168 which adjusts the prediction values Ypredicted, output by the VM model for each of the j non-sampled wafers of the current lot using i historical output measurements (Yhistorical, i) in a weighted manner. The Y2Y adjustment unit 168 adjusts the predictions made by the VM model 166 using historical measurements of Y to capture the L2L tendencies and to smooth the results, filter noises, and maintain predictions close to actual metrology data … In one embodiment, an Exponentially Weighted Moving Average (“EWMA”) is applied to the output data Yhistorical, i, and Ymetrology to Y determine a Y2Y adjustment for the wafers of the current lot 304 … Examiner note: The VM model 166 including the Y2Y adjustment unit 168 corresponds to the control model. The EWMA corresponds to the feedback parameter algorithm, and the Y2Y adjustment determined by applying the EWMA corresponds the process fluctuation because the adjustment accounts for lot-to-lot process tendencies), and applying the process fluctuation to the data output by the model ([0023] Finally, the Y2Y adjusted output values for each of the j wafers of the current lot 404 are calculated as follows: Y2Y adjusted,j=(1−ω)*Y EWMA — current — lot +ω*Y predicted,j where Ypredicted, j is the output value predicted by the VM for wafer j. Examiner note: the reference teaches combining the feedback-derived Y2Y adjustment with predicted model output data Ypredicted,j to produce an adjusted output value. Thus, the reference teaches the technique of applying the calculated process fluctuation to data output by a prediction model).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yoshii in view of Cheng to further incorporate the teaching of Tsai, and apply a lot trend adaptive feedback adjustment to Yoshii’s predicted process model output, in order to account for lot-to-lot process tendencies, smooth noise and maintain the predicted results closer to actual production measurement, thereby improving the accuracy and reliability of the process prediction used for evaluating the manufacturing process.
Claim(s) 5-8 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Yoshii in view of
Cheng and Tsai as applied to claim 4 above, and further in view of Miwa (Reduction of Depth Variation in an Si Etching Process by Applying an Optimized Run-to-Run Control System,” published in 2005).
Claim 5, Yoshii in view of Cheng fails to explicitly teach, but Miwa teaches The method of claim 4, wherein the feedback parameter algorithm comprises one of a moving average algorithm, a weighted moving average algorithm, or an exponential moving average algorithm (Page.518, right column, “Either a simple moving average or exponentially weighted moving average (EWMA) can be used for the control as the moving average (MA) of etch rates (Appendix A).”) .
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Yoshii in view of Cheng and Tsai to incorporated the teaching of Miwa, and apply simple moving average feedback technique as an alternative feedback technique for Run to Run process adjustment, in order to estimate current process behavior based on process data from prior manufacturing lots and compensate for process trends and lot-to-lot variation, thereby reducing process variation and maintaining the controlled process result closer to the target.
Claim 6, Yoshii in view of Cheng and Tsai fails to teach, but Miwa teaches The method of claim 5, wherein the moving average algorithm comprises calculating an average value of process parameters of a plurality of consecutive cycles according to an equation:
PNG
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74
192
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where each of C1, C2,...Cn is a value of the process parameter of a respective cycle, and n is an integer greater than 1 (Page.518, bottom left and top right, “In the RtR control method, the etch rate for wafers in the Nth lot was assumed to be equal to the moving average (MAN) of time series data of the former (N-1, N-2, ---) etched lots as RN = MAN(RN-1, RN-2, …, R1). Either a simple moving average or exponentially weighted moving average (EWMA) can be used for the control as the moving average (MA) of etch rates (Appendix A) …” Page.520, Appendix A,
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256
490
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.
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Yoshii in view of Cheng and Tsai to incorporated the teaching of Miwa, and apply simple moving average feedback technique by averaging process parameter values from a plurality of prior manufacturing cycles, in order to compensate for process trends and lot-to-lot variation, thereby reducing process variation and maintaining the controlled process result closer to the target.
For claims 7, 8 and 12: Claim 5 requires the feedback parameter algorithm to comprise one of a moving average algorithm, a weighted moving average algorithm, or an exponential moving average algorithm. As discussed above, Miwa teaches the moving average algorithm alternative, which is sufficient to meet the limitation of claim 5. Claims 7 and 8 further define the unselected weighted moving average algorithm alternative, and claim 12 further defines the unselected exponential moving average algorithm alternative. Accordingly, the additional limitations of claims 7, 8 and 12 are directed to unselected alternatives of claim 5 and do not come into force with respect to the selected moving average algorithm alternative.
Conclusion
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/YI . HAO/
Examiner, Art Unit 2187
/EMERSON C PUENTE/Supervisory Patent Examiner, Art Unit 2187
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